diff --git a/app.py b/app.py
index 3eb7a2986a3caef889fcec32bcd69fd9218840b5..8458dfd1c9c81b8f1d798201384167aeab897502 100644
--- a/app.py
+++ b/app.py
@@ -83,6 +83,8 @@ def image_to_3d(image: Image.Image) -> Tuple[dict, str]:
     """
     outputs = pipeline(image, formats=["gaussian", "mesh"], preprocess_image=False)
     video = render_utils.render_video(outputs['gaussian'][0], num_frames=120)['color']
+    video_geo = render_utils.render_video(outputs['mesh'][0], num_frames=120)['normal']
+    video = [np.concatenate([video[i], video_geo[i]], axis=1) for i in range(len(video))]
     model_id = uuid.uuid4()
     video_path = f"/tmp/Trellis-demo/{model_id}.mp4"
     os.makedirs(os.path.dirname(video_path), exist_ok=True)
diff --git a/extensions/nvdiffrast/LICENSE.txt b/extensions/nvdiffrast/LICENSE.txt
new file mode 100644
index 0000000000000000000000000000000000000000..26a070a431ce5bb4e926e1289f508f003a4ec730
--- /dev/null
+++ b/extensions/nvdiffrast/LICENSE.txt
@@ -0,0 +1,97 @@
+Copyright (c) 2020, NVIDIA Corporation. All rights reserved.
+
+
+Nvidia Source Code License (1-Way Commercial)
+
+=======================================================================
+
+1. Definitions
+
+"Licensor" means any person or entity that distributes its Work.
+
+"Software" means the original work of authorship made available under
+this License.
+
+"Work" means the Software and any additions to or derivative works of
+the Software that are made available under this License.
+
+The terms "reproduce," "reproduction," "derivative works," and
+"distribution" have the meaning as provided under U.S. copyright law;
+provided, however, that for the purposes of this License, derivative
+works shall not include works that remain separable from, or merely
+link (or bind by name) to the interfaces of, the Work.
+
+Works, including the Software, are "made available" under this License
+by including in or with the Work either (a) a copyright notice
+referencing the applicability of this License to the Work, or (b) a
+copy of this License.
+
+2. License Grants
+
+    2.1 Copyright Grant. Subject to the terms and conditions of this
+    License, each Licensor grants to you a perpetual, worldwide,
+    non-exclusive, royalty-free, copyright license to reproduce,
+    prepare derivative works of, publicly display, publicly perform,
+    sublicense and distribute its Work and any resulting derivative
+    works in any form.
+
+3. Limitations
+
+    3.1 Redistribution. You may reproduce or distribute the Work only
+    if (a) you do so under this License, (b) you include a complete
+    copy of this License with your distribution, and (c) you retain
+    without modification any copyright, patent, trademark, or
+    attribution notices that are present in the Work.
+
+    3.2 Derivative Works. You may specify that additional or different
+    terms apply to the use, reproduction, and distribution of your
+    derivative works of the Work ("Your Terms") only if (a) Your Terms
+    provide that the use limitation in Section 3.3 applies to your
+    derivative works, and (b) you identify the specific derivative
+    works that are subject to Your Terms. Notwithstanding Your Terms,
+    this License (including the redistribution requirements in Section
+    3.1) will continue to apply to the Work itself.
+
+    3.3 Use Limitation. The Work and any derivative works thereof only
+    may be used or intended for use non-commercially. The Work or
+    derivative works thereof may be used or intended for use by Nvidia
+    or its affiliates commercially or non-commercially. As used herein,
+    "non-commercially" means for research or evaluation purposes only
+    and not for any direct or indirect monetary gain.
+
+    3.4 Patent Claims. If you bring or threaten to bring a patent claim
+    against any Licensor (including any claim, cross-claim or
+    counterclaim in a lawsuit) to enforce any patents that you allege
+    are infringed by any Work, then your rights under this License from
+    such Licensor (including the grant in Section 2.1) will terminate
+    immediately.
+
+    3.5 Trademarks. This License does not grant any rights to use any
+    Licensor's or its affiliates' names, logos, or trademarks, except
+    as necessary to reproduce the notices described in this License.
+
+    3.6 Termination. If you violate any term of this License, then your
+    rights under this License (including the grant in Section 2.1) will
+    terminate immediately.
+
+4. Disclaimer of Warranty.
+
+THE WORK IS PROVIDED "AS IS" WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WARRANTIES OR CONDITIONS OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE OR
+NON-INFRINGEMENT. YOU BEAR THE RISK OF UNDERTAKING ANY ACTIVITIES UNDER
+THIS LICENSE.
+
+5. Limitation of Liability.
+
+EXCEPT AS PROHIBITED BY APPLICABLE LAW, IN NO EVENT AND UNDER NO LEGAL
+THEORY, WHETHER IN TORT (INCLUDING NEGLIGENCE), CONTRACT, OR OTHERWISE
+SHALL ANY LICENSOR BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY DIRECT,
+INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF
+OR RELATED TO THIS LICENSE, THE USE OR INABILITY TO USE THE WORK
+(INCLUDING BUT NOT LIMITED TO LOSS OF GOODWILL, BUSINESS INTERRUPTION,
+LOST PROFITS OR DATA, COMPUTER FAILURE OR MALFUNCTION, OR ANY OTHER
+COMMERCIAL DAMAGES OR LOSSES), EVEN IF THE LICENSOR HAS BEEN ADVISED OF
+THE POSSIBILITY OF SUCH DAMAGES.
+
+=======================================================================
diff --git a/extensions/nvdiffrast/README.md b/extensions/nvdiffrast/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..3eeb4115c839a7703c5cac22fe6e89828ad29f2c
--- /dev/null
+++ b/extensions/nvdiffrast/README.md
@@ -0,0 +1,42 @@
+## Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering
+
+![Teaser image](./docs/img/teaser.png)
+
+**Modular Primitives for High-Performance Differentiable Rendering**<br>
+Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, Timo Aila<br>
+[http://arxiv.org/abs/2011.03277](http://arxiv.org/abs/2011.03277)
+
+Nvdiffrast is a PyTorch/TensorFlow library that provides high-performance primitive operations for rasterization-based differentiable rendering.
+Please refer to &#x261E;&#x261E; [nvdiffrast documentation](https://nvlabs.github.io/nvdiffrast) &#x261C;&#x261C; for more information.
+
+## Licenses
+
+Copyright &copy; 2020&ndash;2024, NVIDIA Corporation. All rights reserved.
+
+This work is made available under the [Nvidia Source Code License](https://github.com/NVlabs/nvdiffrast/blob/main/LICENSE.txt).
+
+For business inquiries, please visit our website and submit the form: [NVIDIA Research Licensing](https://www.nvidia.com/en-us/research/inquiries/)
+
+We do not currently accept outside code contributions in the form of pull requests.
+
+Environment map stored as part of `samples/data/envphong.npz` is derived from a Wave Engine
+[sample material](https://github.com/WaveEngine/Samples-2.5/tree/master/Materials/EnvironmentMap/Content/Assets/CubeMap.cubemap)
+originally shared under 
+[MIT License](https://github.com/WaveEngine/Samples-2.5/blob/master/LICENSE.md).
+Mesh and texture stored as part of `samples/data/earth.npz` are derived from
+[3D Earth Photorealistic 2K](https://www.turbosquid.com/3d-models/3d-realistic-earth-photorealistic-2k-1279125)
+model originally made available under
+[TurboSquid 3D Model License](https://blog.turbosquid.com/turbosquid-3d-model-license/#3d-model-license).
+
+## Citation
+
+```
+@article{Laine2020diffrast,
+  title   = {Modular Primitives for High-Performance Differentiable Rendering},
+  author  = {Samuli Laine and Janne Hellsten and Tero Karras and Yeongho Seol and Jaakko Lehtinen and Timo Aila},
+  journal = {ACM Transactions on Graphics},
+  year    = {2020},
+  volume  = {39},
+  number  = {6}
+}
+```
diff --git a/extensions/nvdiffrast/nvdiffrast/__init__.py b/extensions/nvdiffrast/nvdiffrast/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..fd28a0879ef844ef791dca19abdc8416c2468e58
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/__init__.py
@@ -0,0 +1,9 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+__version__ = '0.3.3'
diff --git a/extensions/nvdiffrast/nvdiffrast/common/antialias.cu b/extensions/nvdiffrast/nvdiffrast/common/antialias.cu
new file mode 100644
index 0000000000000000000000000000000000000000..95cc3bab582661a7deb6064daa616adf7121ea36
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/antialias.cu
@@ -0,0 +1,558 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "antialias.h"
+
+//------------------------------------------------------------------------
+// Helpers.
+
+#define F32_MAX (3.402823466e+38f)
+static __forceinline__ __device__ bool same_sign(float a, float b) { return (__float_as_int(a) ^ __float_as_int(b)) >= 0; }
+static __forceinline__ __device__ bool rational_gt(float n0, float n1, float d0, float d1) { return (n0*d1 > n1*d0) == same_sign(d0, d1); }
+static __forceinline__ __device__ int max_idx3(float n0, float n1, float n2, float d0, float d1, float d2)
+{
+    bool g10 = rational_gt(n1, n0, d1, d0);
+    bool g20 = rational_gt(n2, n0, d2, d0);
+    bool g21 = rational_gt(n2, n1, d2, d1);
+    if (g20 && g21) return 2;
+    if (g10) return 1;
+    return 0;
+}
+
+//------------------------------------------------------------------------
+// Format of antialiasing work items stored in work buffer. Usually accessed directly as int4.
+
+struct AAWorkItem
+{
+    enum
+    {
+        EDGE_MASK       = 3,    // Edge index in lowest bits.
+        FLAG_DOWN_BIT   = 2,    // Down instead of right.
+        FLAG_TRI1_BIT   = 3,    // Edge is from other pixel's triangle.
+    };
+
+    int             px, py;         // Pixel x, y.
+    unsigned int    pz_flags;       // High 16 bits = pixel z, low 16 bits = edge index and flags.
+    float           alpha;          // Antialiasing alpha value. Zero if no AA.
+};
+
+//------------------------------------------------------------------------
+// Hash functions. Adapted from public-domain code at http://www.burtleburtle.net/bob/hash/doobs.html
+
+#define JENKINS_MAGIC (0x9e3779b9u)
+static __device__ __forceinline__ void jenkins_mix(unsigned int& a, unsigned int& b, unsigned int& c)
+{
+    a -= b; a -= c; a ^= (c>>13);
+    b -= c; b -= a; b ^= (a<<8);
+    c -= a; c -= b; c ^= (b>>13);
+    a -= b; a -= c; a ^= (c>>12);
+    b -= c; b -= a; b ^= (a<<16);
+    c -= a; c -= b; c ^= (b>>5);
+    a -= b; a -= c; a ^= (c>>3);
+    b -= c; b -= a; b ^= (a<<10);
+    c -= a; c -= b; c ^= (b>>15);
+}
+
+// Helper class for hash index iteration. Implements simple odd-skip linear probing with a key-dependent skip.
+class HashIndex
+{
+public:
+    __device__ __forceinline__ HashIndex(const AntialiasKernelParams& p, uint64_t key)
+    {
+        m_mask = (p.allocTriangles << AA_LOG_HASH_ELEMENTS_PER_TRIANGLE(p.allocTriangles)) - 1; // This should work until triangle count exceeds 1073741824.
+        m_idx  = (uint32_t)(key & 0xffffffffu);
+        m_skip = (uint32_t)(key >> 32);
+        uint32_t dummy = JENKINS_MAGIC;
+        jenkins_mix(m_idx, m_skip, dummy);
+        m_idx &= m_mask;
+        m_skip &= m_mask;
+        m_skip |= 1;
+    }
+    __device__ __forceinline__ int get(void) const { return m_idx; }
+    __device__ __forceinline__ void next(void) { m_idx = (m_idx + m_skip) & m_mask; }
+private:
+    uint32_t m_idx, m_skip, m_mask;
+};
+
+static __device__ __forceinline__ void hash_insert(const AntialiasKernelParams& p, uint64_t key, int v)
+{
+    HashIndex idx(p, key);
+    while(1)
+    {
+        uint64_t prev = atomicCAS((unsigned long long*)&p.evHash[idx.get()], 0, (unsigned long long)key);
+        if (prev == 0 || prev == key)
+            break;
+        idx.next();
+    }
+    int* q = (int*)&p.evHash[idx.get()];
+    int a = atomicCAS(q+2, 0, v);
+    if (a != 0 && a != v)
+        atomicCAS(q+3, 0, v);
+}
+
+static __device__ __forceinline__ int2 hash_find(const AntialiasKernelParams& p, uint64_t key)
+{
+    HashIndex idx(p, key);
+    while(1)
+    {
+        uint4 entry = p.evHash[idx.get()];
+        uint64_t k = ((uint64_t)entry.x) | (((uint64_t)entry.y) << 32);
+        if (k == key || k == 0)
+            return make_int2((int)entry.z, (int)entry.w);
+        idx.next();
+    }
+}
+
+static __device__ __forceinline__ void evhash_insert_vertex(const AntialiasKernelParams& p, int va, int vb, int vn)
+{
+    if (va == vb)
+        return;
+    
+    uint64_t v0 = (uint32_t)min(va, vb) + 1; // canonical vertex order
+    uint64_t v1 = (uint32_t)max(va, vb) + 1;
+    uint64_t vk = v0 | (v1 << 32); // hash key
+    hash_insert(p, vk, vn + 1);
+}
+
+static __forceinline__ __device__ int evhash_find_vertex(const AntialiasKernelParams& p, int va, int vb, int vr)
+{
+    if (va == vb)
+        return -1;
+
+    uint64_t v0 = (uint32_t)min(va, vb) + 1; // canonical vertex order
+    uint64_t v1 = (uint32_t)max(va, vb) + 1;
+    uint64_t vk = v0 | (v1 << 32); // hash key
+    int2 vn = hash_find(p, vk) - 1;
+    if (vn.x == vr) return vn.y;
+    if (vn.y == vr) return vn.x;
+    return -1;
+}
+
+//------------------------------------------------------------------------
+// Mesh analysis kernel.
+
+__global__ void AntialiasFwdMeshKernel(const AntialiasKernelParams p)
+{
+    int idx = threadIdx.x + blockIdx.x * blockDim.x;
+    if (idx >= p.numTriangles)
+        return;
+
+    int v0 = p.tri[idx * 3 + 0];
+    int v1 = p.tri[idx * 3 + 1];
+    int v2 = p.tri[idx * 3 + 2];
+
+    if (v0 < 0 || v0 >= p.numVertices ||
+        v1 < 0 || v1 >= p.numVertices ||
+        v2 < 0 || v2 >= p.numVertices)
+        return;
+
+    if (v0 == v1 || v1 == v2 || v2 == v0)
+        return;
+
+    evhash_insert_vertex(p, v1, v2, v0);
+    evhash_insert_vertex(p, v2, v0, v1);
+    evhash_insert_vertex(p, v0, v1, v2);
+}
+
+//------------------------------------------------------------------------
+// Discontinuity finder kernel.
+
+__global__ void AntialiasFwdDiscontinuityKernel(const AntialiasKernelParams p)
+{
+    // Calculate pixel position.
+    int px = blockIdx.x * AA_DISCONTINUITY_KERNEL_BLOCK_WIDTH + threadIdx.x;
+    int py = blockIdx.y * AA_DISCONTINUITY_KERNEL_BLOCK_HEIGHT + threadIdx.y;
+    int pz = blockIdx.z;
+    if (px >= p.width || py >= p.height || pz >= p.n)
+        return;
+
+    // Pointer to our TriIdx and fetch.
+    int pidx0 = ((px + p.width * (py + p.height * pz)) << 2) + 3;
+    float tri0 = p.rasterOut[pidx0]; // These can stay as float, as we only compare them against each other.
+
+    // Look right, clamp at edge.
+    int pidx1 = pidx0;
+    if (px < p.width - 1)
+        pidx1 += 4;
+    float tri1 = p.rasterOut[pidx1];
+
+    // Look down, clamp at edge.
+    int pidx2 = pidx0;
+    if (py < p.height - 1)
+        pidx2 += p.width << 2;
+    float tri2 = p.rasterOut[pidx2];
+
+    // Determine amount of work.
+    int count = 0;
+    if (tri1 != tri0) count  = 1;
+    if (tri2 != tri0) count += 1;
+    if (!count)
+        return; // Exit warp.
+
+    // Coalesce work counter update to once per CTA.
+    __shared__ int s_temp;
+    s_temp = 0;
+    __syncthreads();
+    int idx = atomicAdd(&s_temp, count);
+    __syncthreads();
+    if (idx == 0)
+    {
+        int base = atomicAdd(&p.workBuffer[0].x, s_temp);
+        s_temp = base + 1; // don't clobber the counters in first slot.
+    }
+    __syncthreads();
+    idx += s_temp;
+
+    // Write to memory.
+    if (tri1 != tri0) p.workBuffer[idx++] = make_int4(px, py, (pz << 16), 0);
+    if (tri2 != tri0) p.workBuffer[idx]   = make_int4(px, py, (pz << 16) + (1 << AAWorkItem::FLAG_DOWN_BIT), 0);
+}
+
+//------------------------------------------------------------------------
+// Forward analysis kernel.
+
+__global__ void AntialiasFwdAnalysisKernel(const AntialiasKernelParams p)
+{
+    __shared__ int s_base;
+    int workCount = p.workBuffer[0].x;
+    for(;;)
+    {
+        // Persistent threads work fetcher.
+        __syncthreads();
+        if (threadIdx.x == 0)
+            s_base = atomicAdd(&p.workBuffer[0].y, AA_ANALYSIS_KERNEL_THREADS_PER_BLOCK);
+        __syncthreads();
+        int thread_idx = s_base + threadIdx.x;
+        if (thread_idx >= workCount)
+            return;
+
+        int4* pItem = p.workBuffer + thread_idx + 1;
+        int4 item = *pItem;
+        int px = item.x;
+        int py = item.y;
+        int pz = (int)(((unsigned int)item.z) >> 16);
+        int d  = (item.z >> AAWorkItem::FLAG_DOWN_BIT) & 1;
+
+        int pixel0 = px + p.width * (py + p.height * pz);
+        int pixel1 = pixel0 + (d ? p.width : 1);
+        float2 zt0 = ((float2*)p.rasterOut)[(pixel0 << 1) + 1];
+        float2 zt1 = ((float2*)p.rasterOut)[(pixel1 << 1) + 1];
+        int tri0 = float_to_triidx(zt0.y) - 1;
+        int tri1 = float_to_triidx(zt1.y) - 1;
+
+        // Select triangle based on background / depth.
+        int tri = (tri0 >= 0) ? tri0 : tri1;
+        if (tri0 >= 0 && tri1 >= 0)
+            tri = (zt0.x < zt1.x) ? tri0 : tri1;
+        if (tri == tri1)
+        {
+            // Calculate with respect to neighbor pixel if chose that triangle.
+            px += 1 - d;
+            py += d;
+        }
+
+        // Bail out if triangle index is corrupt.
+        if (tri < 0 || tri >= p.numTriangles)
+            continue;
+
+        // Fetch vertex indices.
+        int vi0 = p.tri[tri * 3 + 0];
+        int vi1 = p.tri[tri * 3 + 1];
+        int vi2 = p.tri[tri * 3 + 2];
+
+        // Bail out if vertex indices are corrupt.
+        if (vi0 < 0 || vi0 >= p.numVertices ||
+            vi1 < 0 || vi1 >= p.numVertices ||
+            vi2 < 0 || vi2 >= p.numVertices)
+            continue;
+
+        // Fetch opposite vertex indices. Use vertex itself (always silhouette) if no opposite vertex exists.
+        int op0 = evhash_find_vertex(p, vi2, vi1, vi0);
+        int op1 = evhash_find_vertex(p, vi0, vi2, vi1);
+        int op2 = evhash_find_vertex(p, vi1, vi0, vi2);
+
+        // Instance mode: Adjust vertex indices based on minibatch index.
+        if (p.instance_mode)
+        {
+            int vbase = pz * p.numVertices;
+            vi0 += vbase;
+            vi1 += vbase;
+            vi2 += vbase;
+            if (op0 >= 0) op0 += vbase;
+            if (op1 >= 0) op1 += vbase;
+            if (op2 >= 0) op2 += vbase;
+        }
+
+        // Fetch vertex positions.
+        float4 p0 = ((float4*)p.pos)[vi0];
+        float4 p1 = ((float4*)p.pos)[vi1];
+        float4 p2 = ((float4*)p.pos)[vi2];
+        float4 o0 = (op0 < 0) ? p0 : ((float4*)p.pos)[op0];
+        float4 o1 = (op1 < 0) ? p1 : ((float4*)p.pos)[op1];
+        float4 o2 = (op2 < 0) ? p2 : ((float4*)p.pos)[op2];
+
+        // Project vertices to pixel space.
+        float w0  = 1.f / p0.w;
+        float w1  = 1.f / p1.w;
+        float w2  = 1.f / p2.w;
+        float ow0 = 1.f / o0.w;
+        float ow1 = 1.f / o1.w;
+        float ow2 = 1.f / o2.w;
+        float fx  = (float)px + .5f - p.xh;
+        float fy  = (float)py + .5f - p.yh;
+        float x0  = p0.x * w0 * p.xh - fx;
+        float y0  = p0.y * w0 * p.yh - fy;
+        float x1  = p1.x * w1 * p.xh - fx;
+        float y1  = p1.y * w1 * p.yh - fy;
+        float x2  = p2.x * w2 * p.xh - fx;
+        float y2  = p2.y * w2 * p.yh - fy;
+        float ox0 = o0.x * ow0 * p.xh - fx;
+        float oy0 = o0.y * ow0 * p.yh - fy;
+        float ox1 = o1.x * ow1 * p.xh - fx;
+        float oy1 = o1.y * ow1 * p.yh - fy;
+        float ox2 = o2.x * ow2 * p.xh - fx;
+        float oy2 = o2.y * ow2 * p.yh - fy;
+
+        // Signs to kill non-silhouette edges.
+        float bb = (x1-x0)*(y2-y0) - (x2-x0)*(y1-y0); // Triangle itself.
+        float a0 = (x1-ox0)*(y2-oy0) - (x2-ox0)*(y1-oy0); // Wings.
+        float a1 = (x2-ox1)*(y0-oy1) - (x0-ox1)*(y2-oy1);
+        float a2 = (x0-ox2)*(y1-oy2) - (x1-ox2)*(y0-oy2);
+
+        // If no matching signs anywhere, skip the rest.
+        if (same_sign(a0, bb) || same_sign(a1, bb) || same_sign(a2, bb))
+        {
+            // XY flip for horizontal edges.
+            if (d)
+            {
+                swap(x0, y0);
+                swap(x1, y1);
+                swap(x2, y2);
+            }
+
+            float dx0 = x2 - x1;
+            float dx1 = x0 - x2;
+            float dx2 = x1 - x0;
+            float dy0 = y2 - y1;
+            float dy1 = y0 - y2;
+            float dy2 = y1 - y0;
+
+            // Check if an edge crosses between us and the neighbor pixel.
+            float dc = -F32_MAX;
+            float ds = (tri == tri0) ? 1.f : -1.f;
+            float d0 = ds * (x1*dy0 - y1*dx0);
+            float d1 = ds * (x2*dy1 - y2*dx1);
+            float d2 = ds * (x0*dy2 - y0*dx2);
+
+            if (same_sign(y1, y2)) d0 = -F32_MAX, dy0 = 1.f;
+            if (same_sign(y2, y0)) d1 = -F32_MAX, dy1 = 1.f;
+            if (same_sign(y0, y1)) d2 = -F32_MAX, dy2 = 1.f;
+
+            int di = max_idx3(d0, d1, d2, dy0, dy1, dy2);
+            if (di == 0 && same_sign(a0, bb) && fabsf(dy0) >= fabsf(dx0)) dc = d0 / dy0;
+            if (di == 1 && same_sign(a1, bb) && fabsf(dy1) >= fabsf(dx1)) dc = d1 / dy1;
+            if (di == 2 && same_sign(a2, bb) && fabsf(dy2) >= fabsf(dx2)) dc = d2 / dy2;
+            float eps = .0625f; // Expect no more than 1/16 pixel inaccuracy.
+
+            // Adjust output image if a suitable edge was found.
+            if (dc > -eps && dc < 1.f + eps)
+            {
+                dc = fminf(fmaxf(dc, 0.f), 1.f);
+                float alpha = ds * (.5f - dc);
+                const float* pColor0 = p.color + pixel0 * p.channels;
+                const float* pColor1 = p.color + pixel1 * p.channels;
+                float* pOutput = p.output + (alpha > 0.f ? pixel0 : pixel1) * p.channels;
+                for (int i=0; i < p.channels; i++)
+                    atomicAdd(&pOutput[i], alpha * (pColor1[i] - pColor0[i]));
+
+                // Rewrite the work item's flags and alpha. Keep original px, py.
+                unsigned int flags = pz << 16;
+                flags |= di;
+                flags |= d << AAWorkItem::FLAG_DOWN_BIT;
+                flags |= (__float_as_uint(ds) >> 31) << AAWorkItem::FLAG_TRI1_BIT;
+                ((int2*)pItem)[1] = make_int2(flags, __float_as_int(alpha));
+            }
+        }
+    }
+}
+
+//------------------------------------------------------------------------
+// Gradient kernel.
+
+__global__ void AntialiasGradKernel(const AntialiasKernelParams p)
+{
+    // Temporary space for coalesced atomics.
+    CA_DECLARE_TEMP(AA_GRAD_KERNEL_THREADS_PER_BLOCK);
+    __shared__ int s_base; // Work counter communication across entire CTA.
+
+    int workCount = p.workBuffer[0].x;
+
+    for(;;)
+    {
+        // Persistent threads work fetcher.
+        __syncthreads();
+        if (threadIdx.x == 0)
+            s_base = atomicAdd(&p.workBuffer[0].y, AA_GRAD_KERNEL_THREADS_PER_BLOCK);
+        __syncthreads();
+        int thread_idx = s_base + threadIdx.x;
+        if (thread_idx >= workCount)
+            return;
+
+        // Read work item filled out by forward kernel.
+        int4 item = p.workBuffer[thread_idx + 1];
+        unsigned int amask = __ballot_sync(0xffffffffu, item.w);
+        if (item.w == 0)
+            continue; // No effect.
+
+        // Unpack work item and replicate setup from forward analysis kernel.
+        int px = item.x;
+        int py = item.y;
+        int pz = (int)(((unsigned int)item.z) >> 16);
+        int d = (item.z >> AAWorkItem::FLAG_DOWN_BIT) & 1;
+        float alpha = __int_as_float(item.w);
+        int tri1 = (item.z >> AAWorkItem::FLAG_TRI1_BIT) & 1;
+        int di = item.z & AAWorkItem::EDGE_MASK;
+        float ds = __int_as_float(__float_as_int(1.0) | (tri1 << 31));
+        int pixel0 = px + p.width * (py + p.height * pz);
+        int pixel1 = pixel0 + (d ? p.width : 1);
+        int tri = float_to_triidx(p.rasterOut[((tri1 ? pixel1 : pixel0) << 2) + 3]) - 1;
+        if (tri1)
+        {
+            px += 1 - d;
+            py += d;
+        }
+
+        // Bail out if triangle index is corrupt.
+        bool triFail = (tri < 0 || tri >= p.numTriangles);
+        amask = __ballot_sync(amask, !triFail);
+        if (triFail)
+            continue;
+
+        // Outgoing color gradients.
+        float* pGrad0 = p.gradColor + pixel0 * p.channels;
+        float* pGrad1 = p.gradColor + pixel1 * p.channels;
+
+        // Incoming color gradients.
+        const float* pDy = p.dy + (alpha > 0.f ? pixel0 : pixel1) * p.channels;
+
+        // Position gradient weight based on colors and incoming gradients.
+        float dd = 0.f;
+        const float* pColor0 = p.color + pixel0 * p.channels;
+        const float* pColor1 = p.color + pixel1 * p.channels;
+
+        // Loop over channels and accumulate.
+        for (int i=0; i < p.channels; i++)
+        {
+            float dy = pDy[i];
+            if (dy != 0.f)
+            {
+                // Update position gradient weight.
+                dd += dy * (pColor1[i] - pColor0[i]);
+
+                // Update color gradients. No coalescing because all have different targets.
+                float v = alpha * dy;
+                atomicAdd(&pGrad0[i], -v);
+                atomicAdd(&pGrad1[i], v);
+            }
+        }
+
+        // If position weight is zero, skip the rest.
+        bool noGrad = (dd == 0.f);
+        amask = __ballot_sync(amask, !noGrad);
+        if (noGrad)
+            continue;
+
+        // Fetch vertex indices of the active edge and their positions.
+        int i1 = (di < 2) ? (di + 1) : 0;
+        int i2 = (i1 < 2) ? (i1 + 1) : 0;
+        int vi1 = p.tri[3 * tri + i1];
+        int vi2 = p.tri[3 * tri + i2];
+
+        // Bail out if vertex indices are corrupt.
+        bool vtxFail = (vi1 < 0 || vi1 >= p.numVertices || vi2 < 0 || vi2 >= p.numVertices);
+        amask = __ballot_sync(amask, !vtxFail);
+        if (vtxFail)
+            continue;
+
+        // Instance mode: Adjust vertex indices based on minibatch index.
+        if (p.instance_mode)
+        {
+            vi1 += pz * p.numVertices;
+            vi2 += pz * p.numVertices;
+        }
+
+        // Fetch vertex positions.
+        float4 p1 = ((float4*)p.pos)[vi1];
+        float4 p2 = ((float4*)p.pos)[vi2];
+
+        // Project vertices to pixel space.
+        float pxh = p.xh;
+        float pyh = p.yh;
+        float fx = (float)px + .5f - pxh;
+        float fy = (float)py + .5f - pyh;
+
+        // XY flip for horizontal edges.
+        if (d)
+        {
+            swap(p1.x, p1.y);
+            swap(p2.x, p2.y);
+            swap(pxh, pyh);
+            swap(fx, fy);
+        }
+
+        // Gradient calculation setup.
+        float w1 = 1.f / p1.w;
+        float w2 = 1.f / p2.w;
+        float x1 = p1.x * w1 * pxh - fx;
+        float y1 = p1.y * w1 * pyh - fy;
+        float x2 = p2.x * w2 * pxh - fx;
+        float y2 = p2.y * w2 * pyh - fy;
+        float dx = x2 - x1;
+        float dy = y2 - y1;
+        float db = x1*dy - y1*dx;
+
+        // Compute inverse delta-y with epsilon.
+        float ep = copysignf(1e-3f, dy); // ~1/1000 pixel.
+        float iy = 1.f / (dy + ep);
+
+        // Compute position gradients.
+        float dby = db * iy;
+        float iw1 = -w1 * iy * dd;
+        float iw2 =  w2 * iy * dd;
+        float gp1x = iw1 * pxh * y2;
+        float gp2x = iw2 * pxh * y1;
+        float gp1y = iw1 * pyh * (dby - x2);
+        float gp2y = iw2 * pyh * (dby - x1);
+        float gp1w = -(p1.x * gp1x + p1.y * gp1y) * w1;
+        float gp2w = -(p2.x * gp2x + p2.y * gp2y) * w2;
+
+        // XY flip the gradients.
+        if (d)
+        {
+            swap(gp1x, gp1y);
+            swap(gp2x, gp2y);
+        }
+
+        // Kill position gradients if alpha was saturated.
+        if (fabsf(alpha) >= 0.5f)
+        {
+            gp1x = gp1y = gp1w = 0.f;
+            gp2x = gp2y = gp2w = 0.f;
+        }
+
+        // Initialize coalesced atomics. Match both triangle ID and edge index.
+        // Also note that some threads may be inactive.
+        CA_SET_GROUP_MASK(tri ^ (di << 30), amask);
+
+        // Accumulate gradients.
+        caAtomicAdd3_xyw(p.gradPos + 4 * vi1, gp1x, gp1y, gp1w);
+        caAtomicAdd3_xyw(p.gradPos + 4 * vi2, gp2x, gp2y, gp2w);
+    }
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/antialias.h b/extensions/nvdiffrast/nvdiffrast/common/antialias.h
new file mode 100644
index 0000000000000000000000000000000000000000..a324f2f2efc9e45ff6cb9dc125ce6a56dda47698
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/antialias.h
@@ -0,0 +1,50 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include "common.h"
+
+//------------------------------------------------------------------------
+// Constants and helpers.
+
+#define AA_DISCONTINUITY_KERNEL_BLOCK_WIDTH         32
+#define AA_DISCONTINUITY_KERNEL_BLOCK_HEIGHT        8
+#define AA_ANALYSIS_KERNEL_THREADS_PER_BLOCK        256
+#define AA_MESH_KERNEL_THREADS_PER_BLOCK            256
+#define AA_HASH_ELEMENTS_PER_TRIANGLE(alloc)        ((alloc) >= (2 << 25) ? 4 : 8) // With more than 16777216 triangles (alloc >= 33554432) use smallest possible value of 4 to conserve memory, otherwise use 8 for fewer collisions.
+#define AA_LOG_HASH_ELEMENTS_PER_TRIANGLE(alloc)    ((alloc) >= (2 << 25) ? 2 : 3)
+#define AA_GRAD_KERNEL_THREADS_PER_BLOCK            256
+
+//------------------------------------------------------------------------
+// CUDA kernel params.
+
+struct AntialiasKernelParams
+{
+    const float*    color;          // Incoming color buffer.
+    const float*    rasterOut;      // Incoming rasterizer output buffer.
+    const int*      tri;            // Incoming triangle buffer.
+    const float*    pos;            // Incoming position buffer.
+    float*          output;         // Output buffer of forward kernel.
+    const float*    dy;             // Incoming gradients.
+    float*          gradColor;      // Output buffer, color gradient.
+    float*          gradPos;        // Output buffer, position gradient.
+    int4*           workBuffer;     // Buffer for storing intermediate work items. First item reserved for counters.
+    uint4*          evHash;         // Edge-vertex hash.
+    int             allocTriangles; // Number of triangles accommodated by evHash. Always power of two.
+    int             numTriangles;   // Number of triangles.
+    int             numVertices;    // Number of vertices.
+    int             width;          // Input width.
+    int             height;         // Input height.
+    int             n;              // Minibatch size.
+    int             channels;       // Channel count in color input.
+    float           xh, yh;         // Transfer to pixel space.
+    int             instance_mode;  // 0=normal, 1=instance mode.
+    int             tri_const;      // 1 if triangle array is known to be constant.
+};
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/common.cpp b/extensions/nvdiffrast/nvdiffrast/common/common.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..e566c035bdef66e9b75265a58fb8602b0fa530ca
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/common.cpp
@@ -0,0 +1,60 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include <cuda_runtime.h>
+
+//------------------------------------------------------------------------
+// Block and grid size calculators for kernel launches.
+
+dim3 getLaunchBlockSize(int maxWidth, int maxHeight, int width, int height)
+{
+    int maxThreads = maxWidth * maxHeight;
+    if (maxThreads <= 1 || (width * height) <= 1)
+        return dim3(1, 1, 1); // Degenerate.
+
+    // Start from max size.
+    int bw = maxWidth;
+    int bh = maxHeight;
+
+    // Optimizations for weirdly sized buffers.
+    if (width < bw)
+    {
+        // Decrease block width to smallest power of two that covers the buffer width.
+        while ((bw >> 1) >= width)
+            bw >>= 1;
+
+        // Maximize height.
+        bh = maxThreads / bw;
+        if (bh > height)
+            bh = height;
+    }
+    else if (height < bh)
+    {
+        // Halve height and double width until fits completely inside buffer vertically.
+        while (bh > height)
+        {
+            bh >>= 1;
+            if (bw < width)
+                bw <<= 1;
+        }
+    }
+
+    // Done.
+    return dim3(bw, bh, 1);
+}
+
+dim3 getLaunchGridSize(dim3 blockSize, int width, int height, int depth)
+{
+    dim3 gridSize;
+    gridSize.x = (width  - 1) / blockSize.x + 1;
+    gridSize.y = (height - 1) / blockSize.y + 1;
+    gridSize.z = (depth  - 1) / blockSize.z + 1;
+    return gridSize;
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/common.h b/extensions/nvdiffrast/nvdiffrast/common/common.h
new file mode 100644
index 0000000000000000000000000000000000000000..01ecf9fc009081eaaa86c32c7959b599e360cfc7
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/common.h
@@ -0,0 +1,263 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include <cuda.h>
+#include <stdint.h>
+
+//------------------------------------------------------------------------
+// C++ helper function prototypes.
+
+dim3 getLaunchBlockSize(int maxWidth, int maxHeight, int width, int height);
+dim3 getLaunchGridSize(dim3 blockSize, int width, int height, int depth);
+
+//------------------------------------------------------------------------
+// The rest is CUDA device code specific stuff.
+
+#ifdef __CUDACC__
+
+//------------------------------------------------------------------------
+// Helpers for CUDA vector types.
+
+static __device__ __forceinline__ float2&   operator*=  (float2& a, const float2& b)       { a.x *= b.x; a.y *= b.y; return a; }
+static __device__ __forceinline__ float2&   operator+=  (float2& a, const float2& b)       { a.x += b.x; a.y += b.y; return a; }
+static __device__ __forceinline__ float2&   operator-=  (float2& a, const float2& b)       { a.x -= b.x; a.y -= b.y; return a; }
+static __device__ __forceinline__ float2&   operator*=  (float2& a, float b)               { a.x *= b; a.y *= b; return a; }
+static __device__ __forceinline__ float2&   operator+=  (float2& a, float b)               { a.x += b; a.y += b; return a; }
+static __device__ __forceinline__ float2&   operator-=  (float2& a, float b)               { a.x -= b; a.y -= b; return a; }
+static __device__ __forceinline__ float2    operator*   (const float2& a, const float2& b) { return make_float2(a.x * b.x, a.y * b.y); }
+static __device__ __forceinline__ float2    operator+   (const float2& a, const float2& b) { return make_float2(a.x + b.x, a.y + b.y); }
+static __device__ __forceinline__ float2    operator-   (const float2& a, const float2& b) { return make_float2(a.x - b.x, a.y - b.y); }
+static __device__ __forceinline__ float2    operator*   (const float2& a, float b)         { return make_float2(a.x * b, a.y * b); }
+static __device__ __forceinline__ float2    operator+   (const float2& a, float b)         { return make_float2(a.x + b, a.y + b); }
+static __device__ __forceinline__ float2    operator-   (const float2& a, float b)         { return make_float2(a.x - b, a.y - b); }
+static __device__ __forceinline__ float2    operator*   (float a, const float2& b)         { return make_float2(a * b.x, a * b.y); }
+static __device__ __forceinline__ float2    operator+   (float a, const float2& b)         { return make_float2(a + b.x, a + b.y); }
+static __device__ __forceinline__ float2    operator-   (float a, const float2& b)         { return make_float2(a - b.x, a - b.y); }
+static __device__ __forceinline__ float2    operator-   (const float2& a)                  { return make_float2(-a.x, -a.y); }
+static __device__ __forceinline__ float3&   operator*=  (float3& a, const float3& b)       { a.x *= b.x; a.y *= b.y; a.z *= b.z; return a; }
+static __device__ __forceinline__ float3&   operator+=  (float3& a, const float3& b)       { a.x += b.x; a.y += b.y; a.z += b.z; return a; }
+static __device__ __forceinline__ float3&   operator-=  (float3& a, const float3& b)       { a.x -= b.x; a.y -= b.y; a.z -= b.z; return a; }
+static __device__ __forceinline__ float3&   operator*=  (float3& a, float b)               { a.x *= b; a.y *= b; a.z *= b; return a; }
+static __device__ __forceinline__ float3&   operator+=  (float3& a, float b)               { a.x += b; a.y += b; a.z += b; return a; }
+static __device__ __forceinline__ float3&   operator-=  (float3& a, float b)               { a.x -= b; a.y -= b; a.z -= b; return a; }
+static __device__ __forceinline__ float3    operator*   (const float3& a, const float3& b) { return make_float3(a.x * b.x, a.y * b.y, a.z * b.z); }
+static __device__ __forceinline__ float3    operator+   (const float3& a, const float3& b) { return make_float3(a.x + b.x, a.y + b.y, a.z + b.z); }
+static __device__ __forceinline__ float3    operator-   (const float3& a, const float3& b) { return make_float3(a.x - b.x, a.y - b.y, a.z - b.z); }
+static __device__ __forceinline__ float3    operator*   (const float3& a, float b)         { return make_float3(a.x * b, a.y * b, a.z * b); }
+static __device__ __forceinline__ float3    operator+   (const float3& a, float b)         { return make_float3(a.x + b, a.y + b, a.z + b); }
+static __device__ __forceinline__ float3    operator-   (const float3& a, float b)         { return make_float3(a.x - b, a.y - b, a.z - b); }
+static __device__ __forceinline__ float3    operator*   (float a, const float3& b)         { return make_float3(a * b.x, a * b.y, a * b.z); }
+static __device__ __forceinline__ float3    operator+   (float a, const float3& b)         { return make_float3(a + b.x, a + b.y, a + b.z); }
+static __device__ __forceinline__ float3    operator-   (float a, const float3& b)         { return make_float3(a - b.x, a - b.y, a - b.z); }
+static __device__ __forceinline__ float3    operator-   (const float3& a)                  { return make_float3(-a.x, -a.y, -a.z); }
+static __device__ __forceinline__ float4&   operator*=  (float4& a, const float4& b)       { a.x *= b.x; a.y *= b.y; a.z *= b.z; a.w *= b.w; return a; }
+static __device__ __forceinline__ float4&   operator+=  (float4& a, const float4& b)       { a.x += b.x; a.y += b.y; a.z += b.z; a.w += b.w; return a; }
+static __device__ __forceinline__ float4&   operator-=  (float4& a, const float4& b)       { a.x -= b.x; a.y -= b.y; a.z -= b.z; a.w -= b.w; return a; }
+static __device__ __forceinline__ float4&   operator*=  (float4& a, float b)               { a.x *= b; a.y *= b; a.z *= b; a.w *= b; return a; }
+static __device__ __forceinline__ float4&   operator+=  (float4& a, float b)               { a.x += b; a.y += b; a.z += b; a.w += b; return a; }
+static __device__ __forceinline__ float4&   operator-=  (float4& a, float b)               { a.x -= b; a.y -= b; a.z -= b; a.w -= b; return a; }
+static __device__ __forceinline__ float4    operator*   (const float4& a, const float4& b) { return make_float4(a.x * b.x, a.y * b.y, a.z * b.z, a.w * b.w); }
+static __device__ __forceinline__ float4    operator+   (const float4& a, const float4& b) { return make_float4(a.x + b.x, a.y + b.y, a.z + b.z, a.w + b.w); }
+static __device__ __forceinline__ float4    operator-   (const float4& a, const float4& b) { return make_float4(a.x - b.x, a.y - b.y, a.z - b.z, a.w - b.w); }
+static __device__ __forceinline__ float4    operator*   (const float4& a, float b)         { return make_float4(a.x * b, a.y * b, a.z * b, a.w * b); }
+static __device__ __forceinline__ float4    operator+   (const float4& a, float b)         { return make_float4(a.x + b, a.y + b, a.z + b, a.w + b); }
+static __device__ __forceinline__ float4    operator-   (const float4& a, float b)         { return make_float4(a.x - b, a.y - b, a.z - b, a.w - b); }
+static __device__ __forceinline__ float4    operator*   (float a, const float4& b)         { return make_float4(a * b.x, a * b.y, a * b.z, a * b.w); }
+static __device__ __forceinline__ float4    operator+   (float a, const float4& b)         { return make_float4(a + b.x, a + b.y, a + b.z, a + b.w); }
+static __device__ __forceinline__ float4    operator-   (float a, const float4& b)         { return make_float4(a - b.x, a - b.y, a - b.z, a - b.w); }
+static __device__ __forceinline__ float4    operator-   (const float4& a)                  { return make_float4(-a.x, -a.y, -a.z, -a.w); }
+static __device__ __forceinline__ int2&     operator*=  (int2& a, const int2& b)           { a.x *= b.x; a.y *= b.y; return a; }
+static __device__ __forceinline__ int2&     operator+=  (int2& a, const int2& b)           { a.x += b.x; a.y += b.y; return a; }
+static __device__ __forceinline__ int2&     operator-=  (int2& a, const int2& b)           { a.x -= b.x; a.y -= b.y; return a; }
+static __device__ __forceinline__ int2&     operator*=  (int2& a, int b)                   { a.x *= b; a.y *= b; return a; }
+static __device__ __forceinline__ int2&     operator+=  (int2& a, int b)                   { a.x += b; a.y += b; return a; }
+static __device__ __forceinline__ int2&     operator-=  (int2& a, int b)                   { a.x -= b; a.y -= b; return a; }
+static __device__ __forceinline__ int2      operator*   (const int2& a, const int2& b)     { return make_int2(a.x * b.x, a.y * b.y); }
+static __device__ __forceinline__ int2      operator+   (const int2& a, const int2& b)     { return make_int2(a.x + b.x, a.y + b.y); }
+static __device__ __forceinline__ int2      operator-   (const int2& a, const int2& b)     { return make_int2(a.x - b.x, a.y - b.y); }
+static __device__ __forceinline__ int2      operator*   (const int2& a, int b)             { return make_int2(a.x * b, a.y * b); }
+static __device__ __forceinline__ int2      operator+   (const int2& a, int b)             { return make_int2(a.x + b, a.y + b); }
+static __device__ __forceinline__ int2      operator-   (const int2& a, int b)             { return make_int2(a.x - b, a.y - b); }
+static __device__ __forceinline__ int2      operator*   (int a, const int2& b)             { return make_int2(a * b.x, a * b.y); }
+static __device__ __forceinline__ int2      operator+   (int a, const int2& b)             { return make_int2(a + b.x, a + b.y); }
+static __device__ __forceinline__ int2      operator-   (int a, const int2& b)             { return make_int2(a - b.x, a - b.y); }
+static __device__ __forceinline__ int2      operator-   (const int2& a)                    { return make_int2(-a.x, -a.y); }
+static __device__ __forceinline__ int3&     operator*=  (int3& a, const int3& b)           { a.x *= b.x; a.y *= b.y; a.z *= b.z; return a; }
+static __device__ __forceinline__ int3&     operator+=  (int3& a, const int3& b)           { a.x += b.x; a.y += b.y; a.z += b.z; return a; }
+static __device__ __forceinline__ int3&     operator-=  (int3& a, const int3& b)           { a.x -= b.x; a.y -= b.y; a.z -= b.z; return a; }
+static __device__ __forceinline__ int3&     operator*=  (int3& a, int b)                   { a.x *= b; a.y *= b; a.z *= b; return a; }
+static __device__ __forceinline__ int3&     operator+=  (int3& a, int b)                   { a.x += b; a.y += b; a.z += b; return a; }
+static __device__ __forceinline__ int3&     operator-=  (int3& a, int b)                   { a.x -= b; a.y -= b; a.z -= b; return a; }
+static __device__ __forceinline__ int3      operator*   (const int3& a, const int3& b)     { return make_int3(a.x * b.x, a.y * b.y, a.z * b.z); }
+static __device__ __forceinline__ int3      operator+   (const int3& a, const int3& b)     { return make_int3(a.x + b.x, a.y + b.y, a.z + b.z); }
+static __device__ __forceinline__ int3      operator-   (const int3& a, const int3& b)     { return make_int3(a.x - b.x, a.y - b.y, a.z - b.z); }
+static __device__ __forceinline__ int3      operator*   (const int3& a, int b)             { return make_int3(a.x * b, a.y * b, a.z * b); }
+static __device__ __forceinline__ int3      operator+   (const int3& a, int b)             { return make_int3(a.x + b, a.y + b, a.z + b); }
+static __device__ __forceinline__ int3      operator-   (const int3& a, int b)             { return make_int3(a.x - b, a.y - b, a.z - b); }
+static __device__ __forceinline__ int3      operator*   (int a, const int3& b)             { return make_int3(a * b.x, a * b.y, a * b.z); }
+static __device__ __forceinline__ int3      operator+   (int a, const int3& b)             { return make_int3(a + b.x, a + b.y, a + b.z); }
+static __device__ __forceinline__ int3      operator-   (int a, const int3& b)             { return make_int3(a - b.x, a - b.y, a - b.z); }
+static __device__ __forceinline__ int3      operator-   (const int3& a)                    { return make_int3(-a.x, -a.y, -a.z); }
+static __device__ __forceinline__ int4&     operator*=  (int4& a, const int4& b)           { a.x *= b.x; a.y *= b.y; a.z *= b.z; a.w *= b.w; return a; }
+static __device__ __forceinline__ int4&     operator+=  (int4& a, const int4& b)           { a.x += b.x; a.y += b.y; a.z += b.z; a.w += b.w; return a; }
+static __device__ __forceinline__ int4&     operator-=  (int4& a, const int4& b)           { a.x -= b.x; a.y -= b.y; a.z -= b.z; a.w -= b.w; return a; }
+static __device__ __forceinline__ int4&     operator*=  (int4& a, int b)                   { a.x *= b; a.y *= b; a.z *= b; a.w *= b; return a; }
+static __device__ __forceinline__ int4&     operator+=  (int4& a, int b)                   { a.x += b; a.y += b; a.z += b; a.w += b; return a; }
+static __device__ __forceinline__ int4&     operator-=  (int4& a, int b)                   { a.x -= b; a.y -= b; a.z -= b; a.w -= b; return a; }
+static __device__ __forceinline__ int4      operator*   (const int4& a, const int4& b)     { return make_int4(a.x * b.x, a.y * b.y, a.z * b.z, a.w * b.w); }
+static __device__ __forceinline__ int4      operator+   (const int4& a, const int4& b)     { return make_int4(a.x + b.x, a.y + b.y, a.z + b.z, a.w + b.w); }
+static __device__ __forceinline__ int4      operator-   (const int4& a, const int4& b)     { return make_int4(a.x - b.x, a.y - b.y, a.z - b.z, a.w - b.w); }
+static __device__ __forceinline__ int4      operator*   (const int4& a, int b)             { return make_int4(a.x * b, a.y * b, a.z * b, a.w * b); }
+static __device__ __forceinline__ int4      operator+   (const int4& a, int b)             { return make_int4(a.x + b, a.y + b, a.z + b, a.w + b); }
+static __device__ __forceinline__ int4      operator-   (const int4& a, int b)             { return make_int4(a.x - b, a.y - b, a.z - b, a.w - b); }
+static __device__ __forceinline__ int4      operator*   (int a, const int4& b)             { return make_int4(a * b.x, a * b.y, a * b.z, a * b.w); }
+static __device__ __forceinline__ int4      operator+   (int a, const int4& b)             { return make_int4(a + b.x, a + b.y, a + b.z, a + b.w); }
+static __device__ __forceinline__ int4      operator-   (int a, const int4& b)             { return make_int4(a - b.x, a - b.y, a - b.z, a - b.w); }
+static __device__ __forceinline__ int4      operator-   (const int4& a)                    { return make_int4(-a.x, -a.y, -a.z, -a.w); }
+static __device__ __forceinline__ uint2&    operator*=  (uint2& a, const uint2& b)         { a.x *= b.x; a.y *= b.y; return a; }
+static __device__ __forceinline__ uint2&    operator+=  (uint2& a, const uint2& b)         { a.x += b.x; a.y += b.y; return a; }
+static __device__ __forceinline__ uint2&    operator-=  (uint2& a, const uint2& b)         { a.x -= b.x; a.y -= b.y; return a; }
+static __device__ __forceinline__ uint2&    operator*=  (uint2& a, unsigned int b)         { a.x *= b; a.y *= b; return a; }
+static __device__ __forceinline__ uint2&    operator+=  (uint2& a, unsigned int b)         { a.x += b; a.y += b; return a; }
+static __device__ __forceinline__ uint2&    operator-=  (uint2& a, unsigned int b)         { a.x -= b; a.y -= b; return a; }
+static __device__ __forceinline__ uint2     operator*   (const uint2& a, const uint2& b)   { return make_uint2(a.x * b.x, a.y * b.y); }
+static __device__ __forceinline__ uint2     operator+   (const uint2& a, const uint2& b)   { return make_uint2(a.x + b.x, a.y + b.y); }
+static __device__ __forceinline__ uint2     operator-   (const uint2& a, const uint2& b)   { return make_uint2(a.x - b.x, a.y - b.y); }
+static __device__ __forceinline__ uint2     operator*   (const uint2& a, unsigned int b)   { return make_uint2(a.x * b, a.y * b); }
+static __device__ __forceinline__ uint2     operator+   (const uint2& a, unsigned int b)   { return make_uint2(a.x + b, a.y + b); }
+static __device__ __forceinline__ uint2     operator-   (const uint2& a, unsigned int b)   { return make_uint2(a.x - b, a.y - b); }
+static __device__ __forceinline__ uint2     operator*   (unsigned int a, const uint2& b)   { return make_uint2(a * b.x, a * b.y); }
+static __device__ __forceinline__ uint2     operator+   (unsigned int a, const uint2& b)   { return make_uint2(a + b.x, a + b.y); }
+static __device__ __forceinline__ uint2     operator-   (unsigned int a, const uint2& b)   { return make_uint2(a - b.x, a - b.y); }
+static __device__ __forceinline__ uint3&    operator*=  (uint3& a, const uint3& b)         { a.x *= b.x; a.y *= b.y; a.z *= b.z; return a; }
+static __device__ __forceinline__ uint3&    operator+=  (uint3& a, const uint3& b)         { a.x += b.x; a.y += b.y; a.z += b.z; return a; }
+static __device__ __forceinline__ uint3&    operator-=  (uint3& a, const uint3& b)         { a.x -= b.x; a.y -= b.y; a.z -= b.z; return a; }
+static __device__ __forceinline__ uint3&    operator*=  (uint3& a, unsigned int b)         { a.x *= b; a.y *= b; a.z *= b; return a; }
+static __device__ __forceinline__ uint3&    operator+=  (uint3& a, unsigned int b)         { a.x += b; a.y += b; a.z += b; return a; }
+static __device__ __forceinline__ uint3&    operator-=  (uint3& a, unsigned int b)         { a.x -= b; a.y -= b; a.z -= b; return a; }
+static __device__ __forceinline__ uint3     operator*   (const uint3& a, const uint3& b)   { return make_uint3(a.x * b.x, a.y * b.y, a.z * b.z); }
+static __device__ __forceinline__ uint3     operator+   (const uint3& a, const uint3& b)   { return make_uint3(a.x + b.x, a.y + b.y, a.z + b.z); }
+static __device__ __forceinline__ uint3     operator-   (const uint3& a, const uint3& b)   { return make_uint3(a.x - b.x, a.y - b.y, a.z - b.z); }
+static __device__ __forceinline__ uint3     operator*   (const uint3& a, unsigned int b)   { return make_uint3(a.x * b, a.y * b, a.z * b); }
+static __device__ __forceinline__ uint3     operator+   (const uint3& a, unsigned int b)   { return make_uint3(a.x + b, a.y + b, a.z + b); }
+static __device__ __forceinline__ uint3     operator-   (const uint3& a, unsigned int b)   { return make_uint3(a.x - b, a.y - b, a.z - b); }
+static __device__ __forceinline__ uint3     operator*   (unsigned int a, const uint3& b)   { return make_uint3(a * b.x, a * b.y, a * b.z); }
+static __device__ __forceinline__ uint3     operator+   (unsigned int a, const uint3& b)   { return make_uint3(a + b.x, a + b.y, a + b.z); }
+static __device__ __forceinline__ uint3     operator-   (unsigned int a, const uint3& b)   { return make_uint3(a - b.x, a - b.y, a - b.z); }
+static __device__ __forceinline__ uint4&    operator*=  (uint4& a, const uint4& b)         { a.x *= b.x; a.y *= b.y; a.z *= b.z; a.w *= b.w; return a; }
+static __device__ __forceinline__ uint4&    operator+=  (uint4& a, const uint4& b)         { a.x += b.x; a.y += b.y; a.z += b.z; a.w += b.w; return a; }
+static __device__ __forceinline__ uint4&    operator-=  (uint4& a, const uint4& b)         { a.x -= b.x; a.y -= b.y; a.z -= b.z; a.w -= b.w; return a; }
+static __device__ __forceinline__ uint4&    operator*=  (uint4& a, unsigned int b)         { a.x *= b; a.y *= b; a.z *= b; a.w *= b; return a; }
+static __device__ __forceinline__ uint4&    operator+=  (uint4& a, unsigned int b)         { a.x += b; a.y += b; a.z += b; a.w += b; return a; }
+static __device__ __forceinline__ uint4&    operator-=  (uint4& a, unsigned int b)         { a.x -= b; a.y -= b; a.z -= b; a.w -= b; return a; }
+static __device__ __forceinline__ uint4     operator*   (const uint4& a, const uint4& b)   { return make_uint4(a.x * b.x, a.y * b.y, a.z * b.z, a.w * b.w); }
+static __device__ __forceinline__ uint4     operator+   (const uint4& a, const uint4& b)   { return make_uint4(a.x + b.x, a.y + b.y, a.z + b.z, a.w + b.w); }
+static __device__ __forceinline__ uint4     operator-   (const uint4& a, const uint4& b)   { return make_uint4(a.x - b.x, a.y - b.y, a.z - b.z, a.w - b.w); }
+static __device__ __forceinline__ uint4     operator*   (const uint4& a, unsigned int b)   { return make_uint4(a.x * b, a.y * b, a.z * b, a.w * b); }
+static __device__ __forceinline__ uint4     operator+   (const uint4& a, unsigned int b)   { return make_uint4(a.x + b, a.y + b, a.z + b, a.w + b); }
+static __device__ __forceinline__ uint4     operator-   (const uint4& a, unsigned int b)   { return make_uint4(a.x - b, a.y - b, a.z - b, a.w - b); }
+static __device__ __forceinline__ uint4     operator*   (unsigned int a, const uint4& b)   { return make_uint4(a * b.x, a * b.y, a * b.z, a * b.w); }
+static __device__ __forceinline__ uint4     operator+   (unsigned int a, const uint4& b)   { return make_uint4(a + b.x, a + b.y, a + b.z, a + b.w); }
+static __device__ __forceinline__ uint4     operator-   (unsigned int a, const uint4& b)   { return make_uint4(a - b.x, a - b.y, a - b.z, a - b.w); }
+
+template<class T> static __device__ __forceinline__ T zero_value(void);
+template<> __device__ __forceinline__ float  zero_value<float> (void)                      { return 0.f; }
+template<> __device__ __forceinline__ float2 zero_value<float2>(void)                      { return make_float2(0.f, 0.f); }
+template<> __device__ __forceinline__ float4 zero_value<float4>(void)                      { return make_float4(0.f, 0.f, 0.f, 0.f); }
+static __device__ __forceinline__ float3 make_float3(const float2& a, float b)             { return make_float3(a.x, a.y, b); }
+static __device__ __forceinline__ float4 make_float4(const float3& a, float b)             { return make_float4(a.x, a.y, a.z, b); }
+static __device__ __forceinline__ float4 make_float4(const float2& a, const float2& b)     { return make_float4(a.x, a.y, b.x, b.y); }
+static __device__ __forceinline__ int3 make_int3(const int2& a, int b)                     { return make_int3(a.x, a.y, b); }
+static __device__ __forceinline__ int4 make_int4(const int3& a, int b)                     { return make_int4(a.x, a.y, a.z, b); }
+static __device__ __forceinline__ int4 make_int4(const int2& a, const int2& b)             { return make_int4(a.x, a.y, b.x, b.y); }
+static __device__ __forceinline__ uint3 make_uint3(const uint2& a, unsigned int b)         { return make_uint3(a.x, a.y, b); }
+static __device__ __forceinline__ uint4 make_uint4(const uint3& a, unsigned int b)         { return make_uint4(a.x, a.y, a.z, b); }
+static __device__ __forceinline__ uint4 make_uint4(const uint2& a, const uint2& b)         { return make_uint4(a.x, a.y, b.x, b.y); }
+
+template<class T> static __device__ __forceinline__ void swap(T& a, T& b)                  { T temp = a; a = b; b = temp; }
+
+//------------------------------------------------------------------------
+// Triangle ID <-> float32 conversion functions to support very large triangle IDs.
+//
+// Values up to and including 16777216 (also, negative values) are converted trivially and retain
+// compatibility with previous versions. Larger values are mapped to unique float32 that are not equal to
+// the ID. The largest value that converts to float32 and back without generating inf or nan is 889192447.
+
+static __device__ __forceinline__ int   float_to_triidx(float x) { if (x <= 16777216.f) return (int)x;   return __float_as_int(x) - 0x4a800000; }
+static __device__ __forceinline__ float triidx_to_float(int x)   { if (x <= 0x01000000) return (float)x; return __int_as_float(0x4a800000 + x); }
+
+//------------------------------------------------------------------------
+// Coalesced atomics. These are all done via macros.
+
+#if __CUDA_ARCH__ >= 700 // Warp match instruction __match_any_sync() is only available on compute capability 7.x and higher
+
+#define CA_TEMP       _ca_temp
+#define CA_TEMP_PARAM float* CA_TEMP
+#define CA_DECLARE_TEMP(threads_per_block) \
+    __shared__ float CA_TEMP[(threads_per_block)]
+
+#define CA_SET_GROUP_MASK(group, thread_mask)                   \
+    bool   _ca_leader;                                          \
+    float* _ca_ptr;                                             \
+    do {                                                        \
+        int tidx   = threadIdx.x + blockDim.x * threadIdx.y;    \
+        int lane   = tidx & 31;                                 \
+        int warp   = tidx >> 5;                                 \
+        int tmask  = __match_any_sync((thread_mask), (group));  \
+        int leader = __ffs(tmask) - 1;                          \
+        _ca_leader = (leader == lane);                          \
+        _ca_ptr    = &_ca_temp[((warp << 5) + leader)];         \
+    } while(0)
+
+#define CA_SET_GROUP(group) \
+    CA_SET_GROUP_MASK((group), 0xffffffffu)
+
+#define caAtomicAdd(ptr, value)         \
+    do {                                \
+        if (_ca_leader)                 \
+            *_ca_ptr = 0.f;             \
+        atomicAdd(_ca_ptr, (value));    \
+        if (_ca_leader)                 \
+            atomicAdd((ptr), *_ca_ptr); \
+    } while(0)
+
+#define caAtomicAdd3_xyw(ptr, x, y, w)  \
+    do {                                \
+        caAtomicAdd((ptr), (x));        \
+        caAtomicAdd((ptr)+1, (y));      \
+        caAtomicAdd((ptr)+3, (w));      \
+    } while(0)
+
+#define caAtomicAddTexture(ptr, level, idx, value)  \
+    do {                                            \
+        CA_SET_GROUP((idx) ^ ((level) << 27));      \
+        caAtomicAdd((ptr)+(idx), (value));          \
+    } while(0)
+
+//------------------------------------------------------------------------
+// Disable atomic coalescing for compute capability lower than 7.x
+
+#else // __CUDA_ARCH__ >= 700
+#define CA_TEMP _ca_temp
+#define CA_TEMP_PARAM float CA_TEMP
+#define CA_DECLARE_TEMP(threads_per_block) CA_TEMP_PARAM
+#define CA_SET_GROUP_MASK(group, thread_mask)
+#define CA_SET_GROUP(group)
+#define caAtomicAdd(ptr, value) atomicAdd((ptr), (value))
+#define caAtomicAdd3_xyw(ptr, x, y, w)  \
+    do {                                \
+        atomicAdd((ptr), (x));          \
+        atomicAdd((ptr)+1, (y));        \
+        atomicAdd((ptr)+3, (w));        \
+    } while(0)
+#define caAtomicAddTexture(ptr, level, idx, value) atomicAdd((ptr)+(idx), (value))
+#endif // __CUDA_ARCH__ >= 700
+
+//------------------------------------------------------------------------
+#endif // __CUDACC__
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/CudaRaster.hpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/CudaRaster.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..3c1c3a7fd137618d6d20217b5ee4d9b964d3f9b8
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/CudaRaster.hpp
@@ -0,0 +1,63 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+
+//------------------------------------------------------------------------
+// This is a slimmed-down and modernized version of the original
+// CudaRaster codebase that accompanied the HPG 2011 paper
+// "High-Performance Software Rasterization on GPUs" by Laine and Karras.
+// Modifications have been made to accommodate post-Volta execution model
+// with warp divergence. Support for shading, blending, quad rendering,
+// and supersampling have been removed as unnecessary for nvdiffrast.
+//------------------------------------------------------------------------
+
+namespace CR
+{
+
+class RasterImpl;
+
+//------------------------------------------------------------------------
+// Interface class to isolate user from implementation details.
+//------------------------------------------------------------------------
+
+class CudaRaster
+{
+public:
+    enum
+    {
+        RenderModeFlag_EnableBackfaceCulling = 1 << 0,   // Enable backface culling.
+        RenderModeFlag_EnableDepthPeeling    = 1 << 1,   // Enable depth peeling. Must have a peel buffer set.
+    };
+
+public:
+					        CudaRaster				(void);
+					        ~CudaRaster				(void);
+
+    void                    setBufferSize           (int width, int height, int numImages);              // Width and height are internally rounded up to multiples of tile size (8x8) for buffer sizes.
+    void                    setViewport             (int width, int height, int offsetX, int offsetY);   // Tiled rendering viewport setup.
+    void                    setRenderModeFlags      (unsigned int renderModeFlags);                      // Affects all subsequent calls to drawTriangles(). Defaults to zero.
+    void                    deferredClear           (unsigned int clearColor);                           // Clears color and depth buffers during next call to drawTriangles().
+    void                    setVertexBuffer         (void* vertices, int numVertices);                   // GPU pointer managed by caller. Vertex positions in clip space as float4 (x, y, z, w).
+    void                    setIndexBuffer          (void* indices, int numTriangles);                   // GPU pointer managed by caller. Triangle index+color quadruplets as uint4 (idx0, idx1, idx2, color).
+    bool                    drawTriangles           (const int* ranges, bool peel, cudaStream_t stream); // Ranges (offsets and counts) as #triangles entries, not as bytes. If NULL, draw all triangles. Returns false in case of internal overflow.
+    void*                   getColorBuffer          (void);                                              // GPU pointer managed by CudaRaster.
+    void*                   getDepthBuffer          (void);                                              // GPU pointer managed by CudaRaster.
+    void                    swapDepthAndPeel        (void);                                              // Swap depth and peeling buffers.
+
+private:
+					        CudaRaster           	(const CudaRaster&); // forbidden
+	CudaRaster&             operator=           	(const CudaRaster&); // forbidden
+
+private:
+    RasterImpl*             m_impl;                 // Opaque pointer to implementation.
+};
+
+//------------------------------------------------------------------------
+} // namespace CR
+
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/BinRaster.inl b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/BinRaster.inl
new file mode 100644
index 0000000000000000000000000000000000000000..deae9d2c16d780f6cb223fa6a44aa8082003b5ee
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/BinRaster.inl
@@ -0,0 +1,423 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void binRasterImpl(const CRParams p)
+{
+    __shared__ volatile U32 s_broadcast [CR_BIN_WARPS + 16];
+    __shared__ volatile S32 s_outOfs    [CR_MAXBINS_SQR];
+    __shared__ volatile S32 s_outTotal  [CR_MAXBINS_SQR];
+    __shared__ volatile S32 s_overIndex [CR_MAXBINS_SQR];
+    __shared__ volatile S32 s_outMask   [CR_BIN_WARPS][CR_MAXBINS_SQR + 1]; // +1 to avoid bank collisions
+    __shared__ volatile S32 s_outCount  [CR_BIN_WARPS][CR_MAXBINS_SQR + 1]; // +1 to avoid bank collisions
+    __shared__ volatile S32 s_triBuf    [CR_BIN_WARPS*32*4];                // triangle ring buffer
+    __shared__ volatile U32 s_batchPos;
+    __shared__ volatile U32 s_bufCount;
+    __shared__ volatile U32 s_overTotal;
+    __shared__ volatile U32 s_allocBase;
+
+    const CRImageParams&    ip              = getImageParams(p, blockIdx.z);
+    CRAtomics&              atomics         = p.atomics[blockIdx.z];
+    const U8*               triSubtris      = (const U8*)p.triSubtris + p.maxSubtris * blockIdx.z;
+    const CRTriangleHeader* triHeader       = (const CRTriangleHeader*)p.triHeader + p.maxSubtris * blockIdx.z;
+
+    S32*                    binFirstSeg     = (S32*)p.binFirstSeg + CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * blockIdx.z;
+    S32*                    binTotal        = (S32*)p.binTotal    + CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * blockIdx.z;
+    S32*                    binSegData      = (S32*)p.binSegData  + p.maxBinSegs * CR_BIN_SEG_SIZE * blockIdx.z;
+    S32*                    binSegNext      = (S32*)p.binSegNext  + p.maxBinSegs * blockIdx.z;
+    S32*                    binSegCount     = (S32*)p.binSegCount + p.maxBinSegs * blockIdx.z;
+
+    if (atomics.numSubtris > p.maxSubtris)
+        return;
+
+    // per-thread state
+    int thrInBlock = threadIdx.x + threadIdx.y * 32;
+    int batchPos = 0;
+
+    // first 16 elements of s_broadcast are always zero
+    if (thrInBlock < 16)
+        s_broadcast[thrInBlock] = 0;
+
+    // initialize output linked lists and offsets
+    if (thrInBlock < p.numBins)
+    {
+        binFirstSeg[(thrInBlock << CR_BIN_STREAMS_LOG2) + blockIdx.x] = -1;
+        s_outOfs[thrInBlock] = -CR_BIN_SEG_SIZE;
+        s_outTotal[thrInBlock] = 0;
+    }
+
+    // repeat until done
+    for(;;)
+    {
+        // get batch
+        if (thrInBlock == 0)
+            s_batchPos = atomicAdd(&atomics.binCounter, ip.binBatchSize);
+        __syncthreads();
+        batchPos = s_batchPos;
+
+        // all batches done?
+        if (batchPos >= ip.triCount)
+            break;
+
+        // per-thread state
+        int bufIndex = 0;
+        int bufCount = 0;
+        int batchEnd = min(batchPos + ip.binBatchSize, ip.triCount);
+
+        // loop over batch as long as we have triangles in it
+        do
+        {
+            // read more triangles
+            while (bufCount < CR_BIN_WARPS*32 && batchPos < batchEnd)
+            {
+                // get subtriangle count
+
+                int triIdx = batchPos + thrInBlock;
+                int num = 0;
+                if (triIdx < batchEnd)
+                    num = triSubtris[triIdx];
+
+                // cumulative sum of subtriangles within each warp
+                U32 myIdx = __popc(__ballot_sync(~0u, num & 1) & getLaneMaskLt());
+                if (__any_sync(~0u, num > 1))
+                {
+                    myIdx += __popc(__ballot_sync(~0u, num & 2) & getLaneMaskLt()) * 2;
+                    myIdx += __popc(__ballot_sync(~0u, num & 4) & getLaneMaskLt()) * 4;
+                }
+                if (threadIdx.x == 31) // Do not assume that last thread in warp wins the write.
+                    s_broadcast[threadIdx.y + 16] = myIdx + num;
+                __syncthreads();
+
+                // cumulative sum of per-warp subtriangle counts
+                // Note: cannot have more than 32 warps or this needs to sync between each step.
+                bool act = (thrInBlock < CR_BIN_WARPS);
+                U32 actMask = __ballot_sync(~0u, act);
+                if (threadIdx.y == 0 && act)
+                {
+                    volatile U32* ptr = &s_broadcast[thrInBlock + 16];
+                    U32 val = *ptr;
+                    #if (CR_BIN_WARPS > 1)
+                        val += ptr[-1]; __syncwarp(actMask);
+                        *ptr = val;     __syncwarp(actMask);
+                    #endif
+                    #if (CR_BIN_WARPS > 2)
+                        val += ptr[-2]; __syncwarp(actMask);
+                        *ptr = val;     __syncwarp(actMask);
+                    #endif
+                    #if (CR_BIN_WARPS > 4)
+                        val += ptr[-4]; __syncwarp(actMask);
+                        *ptr = val;     __syncwarp(actMask);
+                    #endif
+                    #if (CR_BIN_WARPS > 8)
+                        val += ptr[-8]; __syncwarp(actMask);
+                        *ptr = val;     __syncwarp(actMask);
+                    #endif
+                    #if (CR_BIN_WARPS > 16)
+                        val += ptr[-16]; __syncwarp(actMask);
+                        *ptr = val;      __syncwarp(actMask);
+                    #endif
+
+                    // initially assume that we consume everything
+                    // only last active thread does the writes
+                    if (threadIdx.x == CR_BIN_WARPS - 1)
+                    {
+                        s_batchPos = batchPos + CR_BIN_WARPS * 32;
+                        s_bufCount = bufCount + val;
+                    }
+                }
+                __syncthreads();
+
+                // skip if no subtriangles
+                if (num)
+                {
+                    // calculate write position for first subtriangle
+                    U32 pos = bufCount + myIdx + s_broadcast[threadIdx.y + 16 - 1];
+
+                    // only write if entire triangle fits
+                    if (pos + num <= CR_ARRAY_SIZE(s_triBuf))
+                    {
+                        pos += bufIndex; // adjust for current start position
+                        pos &= CR_ARRAY_SIZE(s_triBuf)-1;
+                        if (num == 1)
+                            s_triBuf[pos] = triIdx * 8 + 7; // single triangle
+                        else
+                        {
+                            for (int i=0; i < num; i++)
+                            {
+                                s_triBuf[pos] = triIdx * 8 + i;
+                                pos++;
+                                pos &= CR_ARRAY_SIZE(s_triBuf)-1;
+                            }
+                        }
+                    } else if (pos <= CR_ARRAY_SIZE(s_triBuf))
+                    {
+                        // this triangle is the first that failed, overwrite total count and triangle count
+                        s_batchPos = batchPos + thrInBlock;
+                        s_bufCount = pos;
+                    }
+                }
+
+                // update triangle counts
+                __syncthreads();
+                batchPos = s_batchPos;
+                bufCount = s_bufCount;
+            }
+
+            // make every warp clear its output buffers
+            for (int i=threadIdx.x; i < p.numBins; i += 32)
+                s_outMask[threadIdx.y][i] = 0;
+            __syncwarp();
+
+            // choose our triangle
+            uint4 triData = make_uint4(0, 0, 0, 0);
+            if (thrInBlock < bufCount)
+            {
+                U32 triPos = bufIndex + thrInBlock;
+                triPos &= CR_ARRAY_SIZE(s_triBuf)-1;
+
+                // find triangle
+                int triIdx = s_triBuf[triPos];
+                int dataIdx = triIdx >> 3;
+                int subtriIdx = triIdx & 7;
+                if (subtriIdx != 7)
+                    dataIdx = triHeader[dataIdx].misc + subtriIdx;
+
+                // read triangle
+
+                triData = *(((const uint4*)triHeader) + dataIdx);
+            }
+
+            // setup bounding box and edge functions, and rasterize
+            S32 lox, loy, hix, hiy;
+            bool hasTri = (thrInBlock < bufCount);
+            U32 hasTriMask = __ballot_sync(~0u, hasTri);
+            if (hasTri)
+            {
+                S32 v0x = add_s16lo_s16lo(triData.x, p.widthPixelsVp  * (CR_SUBPIXEL_SIZE >> 1));
+                S32 v0y = add_s16hi_s16lo(triData.x, p.heightPixelsVp * (CR_SUBPIXEL_SIZE >> 1));
+                S32 d01x = sub_s16lo_s16lo(triData.y, triData.x);
+                S32 d01y = sub_s16hi_s16hi(triData.y, triData.x);
+                S32 d02x = sub_s16lo_s16lo(triData.z, triData.x);
+                S32 d02y = sub_s16hi_s16hi(triData.z, triData.x);
+                int binLog = CR_BIN_LOG2 + CR_TILE_LOG2 + CR_SUBPIXEL_LOG2;
+                lox = add_clamp_0_x((v0x + min_min(d01x, 0, d02x)) >> binLog, 0, p.widthBins  - 1);
+                loy = add_clamp_0_x((v0y + min_min(d01y, 0, d02y)) >> binLog, 0, p.heightBins - 1);
+                hix = add_clamp_0_x((v0x + max_max(d01x, 0, d02x)) >> binLog, 0, p.widthBins  - 1);
+                hiy = add_clamp_0_x((v0y + max_max(d01y, 0, d02y)) >> binLog, 0, p.heightBins - 1);
+
+                U32 bit = 1 << threadIdx.x;
+#if __CUDA_ARCH__ >= 700
+                bool multi = (hix != lox || hiy != loy);
+                if (!__any_sync(hasTriMask, multi))
+                {
+                    int binIdx = lox + p.widthBins * loy;
+                    U32 mask = __match_any_sync(hasTriMask, binIdx);
+                    s_outMask[threadIdx.y][binIdx] = mask;
+                    __syncwarp(hasTriMask);
+                } else
+#endif
+                {
+                    bool complex = (hix > lox+1 || hiy > loy+1);
+                    if (!__any_sync(hasTriMask, complex))
+                    {
+                        int binIdx = lox + p.widthBins * loy;
+                        atomicOr((U32*)&s_outMask[threadIdx.y][binIdx], bit);
+                        if (hix > lox) atomicOr((U32*)&s_outMask[threadIdx.y][binIdx + 1], bit);
+                        if (hiy > loy) atomicOr((U32*)&s_outMask[threadIdx.y][binIdx + p.widthBins], bit);
+                        if (hix > lox && hiy > loy) atomicOr((U32*)&s_outMask[threadIdx.y][binIdx + p.widthBins + 1], bit);
+                    } else
+                    {
+                        S32 d12x = d02x - d01x, d12y = d02y - d01y;
+                        v0x -= lox << binLog, v0y -= loy << binLog;
+
+                        S32 t01 = v0x * d01y - v0y * d01x;
+                        S32 t02 = v0y * d02x - v0x * d02y;
+                        S32 t12 = d01x * d12y - d01y * d12x - t01 - t02;
+                        S32 b01 = add_sub(t01 >> binLog, max(d01x, 0), min(d01y, 0));
+                        S32 b02 = add_sub(t02 >> binLog, max(d02y, 0), min(d02x, 0));
+                        S32 b12 = add_sub(t12 >> binLog, max(d12x, 0), min(d12y, 0));
+
+                        int width = hix - lox + 1;
+                        d01x += width * d01y;
+                        d02x += width * d02y;
+                        d12x += width * d12y;
+
+                        U8* currPtr = (U8*)&s_outMask[threadIdx.y][lox + loy * p.widthBins];
+                        U8* skipPtr = (U8*)&s_outMask[threadIdx.y][(hix + 1) + loy * p.widthBins];
+                        U8* endPtr  = (U8*)&s_outMask[threadIdx.y][lox + (hiy + 1) * p.widthBins];
+                        int stride  = p.widthBins * 4;
+                        int ptrYInc = stride - width * 4;
+
+                        do
+                        {
+                            if (b01 >= 0 && b02 >= 0 && b12 >= 0)
+                                atomicOr((U32*)currPtr, bit);
+                            currPtr += 4, b01 -= d01y, b02 += d02y, b12 -= d12y;
+                            if (currPtr == skipPtr)
+                                currPtr += ptrYInc, b01 += d01x, b02 -= d02x, b12 += d12x, skipPtr += stride;
+                        }
+                        while (currPtr != endPtr);
+                    }
+                }
+            }
+
+            // count per-bin contributions
+            if (thrInBlock == 0)
+                s_overTotal = 0; // overflow counter
+
+            // ensure that out masks are done
+            __syncthreads();
+
+            int overIndex = -1;
+            bool act = (thrInBlock < p.numBins);
+            U32 actMask = __ballot_sync(~0u, act);
+            if (act)
+            {
+                U8* srcPtr = (U8*)&s_outMask[0][thrInBlock];
+                U8* dstPtr = (U8*)&s_outCount[0][thrInBlock];
+                int total = 0;
+                for (int i = 0; i < CR_BIN_WARPS; i++)
+                {
+                    total += __popc(*(U32*)srcPtr);
+                    *(U32*)dstPtr = total;
+                    srcPtr += (CR_MAXBINS_SQR + 1) * 4;
+                    dstPtr += (CR_MAXBINS_SQR + 1) * 4;
+                }
+
+                // overflow => request a new segment
+                int ofs = s_outOfs[thrInBlock];
+                bool ovr = (((ofs - 1) >> CR_BIN_SEG_LOG2) != (((ofs - 1) + total) >> CR_BIN_SEG_LOG2));
+                U32 ovrMask = __ballot_sync(actMask, ovr);
+                if (ovr)
+                {
+                    overIndex = __popc(ovrMask & getLaneMaskLt());
+                    if (overIndex == 0)
+                        s_broadcast[threadIdx.y + 16] = atomicAdd((U32*)&s_overTotal, __popc(ovrMask));
+                    __syncwarp(ovrMask);
+                    overIndex += s_broadcast[threadIdx.y + 16];
+                    s_overIndex[thrInBlock] = overIndex;
+                }
+            }
+
+            // sync after overTotal is ready
+            __syncthreads();
+
+            // at least one segment overflowed => allocate segments
+            U32 overTotal = s_overTotal;
+            U32 allocBase = 0;
+            if (overTotal > 0)
+            {
+                // allocate memory
+                if (thrInBlock == 0)
+                {
+                    U32 allocBase = atomicAdd(&atomics.numBinSegs, overTotal);
+                    s_allocBase = (allocBase + overTotal <= p.maxBinSegs) ? allocBase : 0;
+                }
+                __syncthreads();
+                allocBase = s_allocBase;
+
+                // did my bin overflow?
+                if (overIndex != -1)
+                {
+                    // calculate new segment index
+                    int segIdx = allocBase + overIndex;
+
+                    // add to linked list
+                    if (s_outOfs[thrInBlock] < 0)
+                        binFirstSeg[(thrInBlock << CR_BIN_STREAMS_LOG2) + blockIdx.x] = segIdx;
+                    else
+                        binSegNext[(s_outOfs[thrInBlock] - 1) >> CR_BIN_SEG_LOG2] = segIdx;
+
+                    // defaults
+                    binSegNext [segIdx] = -1;
+                    binSegCount[segIdx] = CR_BIN_SEG_SIZE;
+                }
+            }
+
+            // concurrent emission -- each warp handles its own triangle
+            if (thrInBlock < bufCount)
+            {
+                int triPos  = (bufIndex + thrInBlock) & (CR_ARRAY_SIZE(s_triBuf) - 1);
+                int currBin = lox + loy * p.widthBins;
+                int skipBin = (hix + 1) + loy * p.widthBins;
+                int endBin  = lox + (hiy + 1) * p.widthBins;
+                int binYInc = p.widthBins - (hix - lox + 1);
+
+                // loop over triangle's bins
+                do
+                {
+                    U32 outMask = s_outMask[threadIdx.y][currBin];
+                    if (outMask & (1<<threadIdx.x))
+                    {
+                        int idx = __popc(outMask & getLaneMaskLt());
+                        if (threadIdx.y > 0)
+                            idx += s_outCount[threadIdx.y-1][currBin];
+
+                        int base = s_outOfs[currBin];
+                        int free = (-base) & (CR_BIN_SEG_SIZE - 1);
+                        if (idx >= free)
+                            idx += ((allocBase + s_overIndex[currBin]) << CR_BIN_SEG_LOG2) - free;
+                        else
+                            idx += base;
+
+                        binSegData[idx] = s_triBuf[triPos];
+                    }
+
+                    currBin++;
+                    if (currBin == skipBin)
+                        currBin += binYInc, skipBin += p.widthBins;
+                }
+                while (currBin != endBin);
+            }
+
+            // wait all triangles to finish, then replace overflown segment offsets
+            __syncthreads();
+            if (thrInBlock < p.numBins)
+            {
+                U32 total  = s_outCount[CR_BIN_WARPS - 1][thrInBlock];
+                U32 oldOfs = s_outOfs[thrInBlock];
+                if (overIndex == -1)
+                    s_outOfs[thrInBlock] = oldOfs + total;
+                else
+                {
+                    int addr = oldOfs + total;
+                    addr = ((addr - 1) & (CR_BIN_SEG_SIZE - 1)) + 1;
+                    addr += (allocBase + overIndex) << CR_BIN_SEG_LOG2;
+                    s_outOfs[thrInBlock] = addr;
+                }
+                s_outTotal[thrInBlock] += total;
+            }
+
+            // these triangles are now done
+            int count = ::min(bufCount, CR_BIN_WARPS * 32);
+            bufCount -= count;
+            bufIndex += count;
+            bufIndex &= CR_ARRAY_SIZE(s_triBuf)-1;
+        }
+        while (bufCount > 0 || batchPos < batchEnd);
+
+        // flush all bins
+        if (thrInBlock < p.numBins)
+        {
+            int ofs = s_outOfs[thrInBlock];
+            if (ofs & (CR_BIN_SEG_SIZE-1))
+            {
+                int seg = ofs >> CR_BIN_SEG_LOG2;
+                binSegCount[seg] = ofs & (CR_BIN_SEG_SIZE-1);
+                s_outOfs[thrInBlock] = (ofs + CR_BIN_SEG_SIZE - 1) & -CR_BIN_SEG_SIZE;
+            }
+        }
+    }
+
+    // output totals
+    if (thrInBlock < p.numBins)
+        binTotal[(thrInBlock << CR_BIN_STREAMS_LOG2) + blockIdx.x] = s_outTotal[thrInBlock];
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Buffer.cpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Buffer.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..b2cd7b92ba90964d4d8f66b6a3554d75b1737885
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Buffer.cpp
@@ -0,0 +1,94 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "../../framework.h"
+#include "Buffer.hpp"
+
+using namespace CR;
+
+//------------------------------------------------------------------------
+// GPU buffer.
+//------------------------------------------------------------------------
+
+Buffer::Buffer(void)
+:   m_gpuPtr(NULL),
+    m_bytes (0)
+{
+    // empty
+}
+
+Buffer::~Buffer(void)
+{
+    if (m_gpuPtr)
+        cudaFree(m_gpuPtr); // Don't throw an exception.
+}
+
+void Buffer::reset(size_t bytes)
+{
+    if (bytes == m_bytes)
+        return;
+
+    if (m_gpuPtr)
+    {
+        NVDR_CHECK_CUDA_ERROR(cudaFree(m_gpuPtr));
+        m_gpuPtr = NULL;
+    }
+
+    if (bytes > 0)
+        NVDR_CHECK_CUDA_ERROR(cudaMalloc(&m_gpuPtr, bytes));
+
+    m_bytes = bytes;
+}
+
+void Buffer::grow(size_t bytes)
+{
+    if (bytes > m_bytes)
+        reset(bytes);
+}
+
+//------------------------------------------------------------------------
+// Host buffer with page-locked memory.
+//------------------------------------------------------------------------
+
+HostBuffer::HostBuffer(void)
+:   m_hostPtr(NULL),
+    m_bytes  (0)
+{
+    // empty
+}
+
+HostBuffer::~HostBuffer(void)
+{
+    if (m_hostPtr)
+        cudaFreeHost(m_hostPtr); // Don't throw an exception.
+}
+
+void HostBuffer::reset(size_t bytes)
+{
+    if (bytes == m_bytes)
+        return;
+
+    if (m_hostPtr)
+    {
+        NVDR_CHECK_CUDA_ERROR(cudaFreeHost(m_hostPtr));
+        m_hostPtr = NULL;
+    }
+
+    if (bytes > 0)
+        NVDR_CHECK_CUDA_ERROR(cudaMallocHost(&m_hostPtr, bytes));
+
+    m_bytes = bytes;
+}
+
+void HostBuffer::grow(size_t bytes)
+{
+    if (bytes > m_bytes)
+        reset(bytes);
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Buffer.hpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Buffer.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..8a4b38fdbedf668366c94c0263a61815e62a6a3a
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Buffer.hpp
@@ -0,0 +1,55 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include "Defs.hpp"
+
+namespace CR
+{
+//------------------------------------------------------------------------
+
+class Buffer
+{
+public:
+                    Buffer      (void);
+                    ~Buffer     (void);
+
+    void            reset       (size_t bytes);
+    void            grow        (size_t bytes);
+    void*           getPtr      (size_t offset = 0) { return (void*)(((uintptr_t)m_gpuPtr) + offset); }
+    size_t          getSize     (void) const { return m_bytes; }
+
+    void            setPtr      (void* ptr) { m_gpuPtr = ptr; }
+
+private:
+    void*           m_gpuPtr;
+    size_t          m_bytes;
+};
+
+//------------------------------------------------------------------------
+
+class HostBuffer
+{
+public:
+                    HostBuffer  (void);
+                    ~HostBuffer (void);
+
+    void            reset       (size_t bytes);
+    void            grow        (size_t bytes);
+    void*           getPtr      (void) { return m_hostPtr; }
+    size_t          getSize     (void) const { return m_bytes; }
+
+    void            setPtr      (void* ptr) { m_hostPtr = ptr; }
+
+private:
+    void*           m_hostPtr;
+    size_t          m_bytes;
+};
+
+//------------------------------------------------------------------------
+}
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/CoarseRaster.inl b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/CoarseRaster.inl
new file mode 100644
index 0000000000000000000000000000000000000000..a7081c7e3dee992bbb0223e9008b17a3c69e6387
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/CoarseRaster.inl
@@ -0,0 +1,730 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ int globalTileIdx(int tileInBin, int widthTiles)
+{
+    int tileX = tileInBin & (CR_BIN_SIZE - 1);
+    int tileY = tileInBin >> CR_BIN_LOG2;
+    return tileX + tileY * widthTiles;
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void coarseRasterImpl(const CRParams p)
+{
+    // Common.
+
+    __shared__ volatile U32 s_workCounter;
+    __shared__ volatile U32 s_scanTemp          [CR_COARSE_WARPS][48];              // 3KB
+
+    // Input.
+
+    __shared__ volatile U32 s_binOrder          [CR_MAXBINS_SQR];                   // 1KB
+    __shared__ volatile S32 s_binStreamCurrSeg  [CR_BIN_STREAMS_SIZE];              // 0KB
+    __shared__ volatile S32 s_binStreamFirstTri [CR_BIN_STREAMS_SIZE];              // 0KB
+    __shared__ volatile S32 s_triQueue          [CR_COARSE_QUEUE_SIZE];             // 4KB
+    __shared__ volatile S32 s_triQueueWritePos;
+    __shared__ volatile U32 s_binStreamSelectedOfs;
+    __shared__ volatile U32 s_binStreamSelectedSize;
+
+    // Output.
+
+    __shared__ volatile U32 s_warpEmitMask      [CR_COARSE_WARPS][CR_BIN_SQR + 1];  // 16KB, +1 to avoid bank collisions
+    __shared__ volatile U32 s_warpEmitPrefixSum [CR_COARSE_WARPS][CR_BIN_SQR + 1];  // 16KB, +1 to avoid bank collisions
+    __shared__ volatile U32 s_tileEmitPrefixSum [CR_BIN_SQR + 1];                   // 1KB, zero at the beginning
+    __shared__ volatile U32 s_tileAllocPrefixSum[CR_BIN_SQR + 1];                   // 1KB, zero at the beginning
+    __shared__ volatile S32 s_tileStreamCurrOfs [CR_BIN_SQR];                       // 1KB
+    __shared__ volatile U32 s_firstAllocSeg;
+    __shared__ volatile U32 s_firstActiveIdx;
+
+    // Pointers and constants.
+
+    CRAtomics&              atomics         = p.atomics[blockIdx.z];
+    const CRTriangleHeader* triHeader       = (const CRTriangleHeader*)p.triHeader + p.maxSubtris * blockIdx.z;
+    const S32*              binFirstSeg     = (const S32*)p.binFirstSeg + CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * blockIdx.z;
+    const S32*              binTotal        = (const S32*)p.binTotal    + CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * blockIdx.z;
+    const S32*              binSegData      = (const S32*)p.binSegData  + p.maxBinSegs * CR_BIN_SEG_SIZE * blockIdx.z;
+    const S32*              binSegNext      = (const S32*)p.binSegNext  + p.maxBinSegs * blockIdx.z;
+    const S32*              binSegCount     = (const S32*)p.binSegCount + p.maxBinSegs * blockIdx.z;
+    S32*                    activeTiles     = (S32*)p.activeTiles  + CR_MAXTILES_SQR * blockIdx.z;
+    S32*                    tileFirstSeg    = (S32*)p.tileFirstSeg + CR_MAXTILES_SQR * blockIdx.z;
+    S32*                    tileSegData     = (S32*)p.tileSegData  + p.maxTileSegs * CR_TILE_SEG_SIZE * blockIdx.z;
+    S32*                    tileSegNext     = (S32*)p.tileSegNext  + p.maxTileSegs * blockIdx.z;
+    S32*                    tileSegCount    = (S32*)p.tileSegCount + p.maxTileSegs * blockIdx.z;
+
+    int tileLog     = CR_TILE_LOG2 + CR_SUBPIXEL_LOG2;
+    int thrInBlock  = threadIdx.x + threadIdx.y * 32;
+    int emitShift   = CR_BIN_LOG2 * 2 + 5; // We scan ((numEmits << emitShift) | numAllocs) over tiles.
+
+    if (atomics.numSubtris > p.maxSubtris || atomics.numBinSegs > p.maxBinSegs)
+        return;
+
+    // Initialize sharedmem arrays.
+
+    if (thrInBlock == 0)
+    {
+        s_tileEmitPrefixSum[0] = 0;
+        s_tileAllocPrefixSum[0] = 0;
+    }
+    s_scanTemp[threadIdx.y][threadIdx.x] = 0;
+
+    // Sort bins in descending order of triangle count.
+
+    for (int binIdx = thrInBlock; binIdx < p.numBins; binIdx += CR_COARSE_WARPS * 32)
+    {
+        int count = 0;
+        for (int i = 0; i < CR_BIN_STREAMS_SIZE; i++)
+            count += binTotal[(binIdx << CR_BIN_STREAMS_LOG2) + i];
+        s_binOrder[binIdx] = (~count << (CR_MAXBINS_LOG2 * 2)) | binIdx;
+    }
+
+    __syncthreads();
+    sortShared(s_binOrder, p.numBins);
+
+    // Process each bin by one block.
+
+    for (;;)
+    {
+        // Pick a bin for the block.
+
+        if (thrInBlock == 0)
+            s_workCounter = atomicAdd(&atomics.coarseCounter, 1);
+        __syncthreads();
+
+        int workCounter = s_workCounter;
+        if (workCounter >= p.numBins)
+            break;
+
+        U32 binOrder = s_binOrder[workCounter];
+        bool binEmpty = ((~binOrder >> (CR_MAXBINS_LOG2 * 2)) == 0);
+        if (binEmpty && !p.deferredClear)
+            break;
+
+        int binIdx = binOrder & (CR_MAXBINS_SQR - 1);
+
+        // Initialize input/output streams.
+
+        int triQueueWritePos = 0;
+        int triQueueReadPos = 0;
+
+        if (thrInBlock < CR_BIN_STREAMS_SIZE)
+        {
+            int segIdx = binFirstSeg[(binIdx << CR_BIN_STREAMS_LOG2) + thrInBlock];
+            s_binStreamCurrSeg[thrInBlock] = segIdx;
+            s_binStreamFirstTri[thrInBlock] = (segIdx == -1) ? ~0u : binSegData[segIdx << CR_BIN_SEG_LOG2];
+        }
+
+        for (int tileInBin = CR_COARSE_WARPS * 32 - 1 - thrInBlock; tileInBin < CR_BIN_SQR; tileInBin += CR_COARSE_WARPS * 32)
+            s_tileStreamCurrOfs[tileInBin] = -CR_TILE_SEG_SIZE;
+
+        // Initialize per-bin state.
+
+        int binY = idiv_fast(binIdx, p.widthBins);
+        int binX = binIdx - binY * p.widthBins;
+        int originX = (binX << (CR_BIN_LOG2 + tileLog)) - (p.widthPixelsVp << (CR_SUBPIXEL_LOG2 - 1));
+        int originY = (binY << (CR_BIN_LOG2 + tileLog)) - (p.heightPixelsVp << (CR_SUBPIXEL_LOG2 - 1));
+        int maxTileXInBin = ::min(p.widthTiles - (binX << CR_BIN_LOG2), CR_BIN_SIZE) - 1;
+        int maxTileYInBin = ::min(p.heightTiles - (binY << CR_BIN_LOG2), CR_BIN_SIZE) - 1;
+        int binTileIdx = (binX + binY * p.widthTiles) << CR_BIN_LOG2;
+
+        // Entire block: Merge input streams and process triangles.
+
+        if (!binEmpty)
+        do
+        {
+            //------------------------------------------------------------------------
+            // Merge.
+            //------------------------------------------------------------------------
+
+            // Entire block: Not enough triangles => merge and queue segments.
+            // NOTE: The bin exit criterion assumes that we queue more triangles than we actually need.
+
+            while (triQueueWritePos - triQueueReadPos <= CR_COARSE_WARPS * 32)
+            {
+                // First warp: Choose the segment with the lowest initial triangle index.
+
+                bool hasStream = (thrInBlock < CR_BIN_STREAMS_SIZE);
+                U32 hasStreamMask = __ballot_sync(~0u, hasStream);
+                if (hasStream)
+                {
+                    // Find the stream with the lowest triangle index.
+
+                    U32 firstTri = s_binStreamFirstTri[thrInBlock];
+                    U32 t = firstTri;
+                    volatile U32* v = &s_scanTemp[0][thrInBlock + 16];
+
+                    #if (CR_BIN_STREAMS_SIZE > 1)
+                        v[0] = t; __syncwarp(hasStreamMask); t = ::min(t, v[-1]); __syncwarp(hasStreamMask);
+                    #endif
+                    #if (CR_BIN_STREAMS_SIZE > 2)
+                        v[0] = t; __syncwarp(hasStreamMask); t = ::min(t, v[-2]); __syncwarp(hasStreamMask);
+                    #endif
+                    #if (CR_BIN_STREAMS_SIZE > 4)
+                        v[0] = t; __syncwarp(hasStreamMask); t = ::min(t, v[-4]); __syncwarp(hasStreamMask);
+                    #endif
+                    #if (CR_BIN_STREAMS_SIZE > 8)
+                        v[0] = t; __syncwarp(hasStreamMask); t = ::min(t, v[-8]); __syncwarp(hasStreamMask);
+                    #endif
+                    #if (CR_BIN_STREAMS_SIZE > 16)
+                        v[0] = t; __syncwarp(hasStreamMask); t = ::min(t, v[-16]); __syncwarp(hasStreamMask);
+                    #endif
+                    v[0] = t; __syncwarp(hasStreamMask);
+
+                    // Consume and broadcast.
+
+                    bool first = (s_scanTemp[0][CR_BIN_STREAMS_SIZE - 1 + 16] == firstTri);
+                    U32 firstMask = __ballot_sync(hasStreamMask, first);
+                    if (first && (firstMask >> threadIdx.x) == 1u)
+                    {
+                        int segIdx = s_binStreamCurrSeg[thrInBlock];
+                        s_binStreamSelectedOfs = segIdx << CR_BIN_SEG_LOG2;
+                        if (segIdx != -1)
+                        {
+                            int segSize = binSegCount[segIdx];
+                            int segNext = binSegNext[segIdx];
+                            s_binStreamSelectedSize = segSize;
+                            s_triQueueWritePos = triQueueWritePos + segSize;
+                            s_binStreamCurrSeg[thrInBlock] = segNext;
+                            s_binStreamFirstTri[thrInBlock] = (segNext == -1) ? ~0u : binSegData[segNext << CR_BIN_SEG_LOG2];
+                        }
+                    }
+                }
+
+                // No more segments => break.
+
+                __syncthreads();
+                triQueueWritePos = s_triQueueWritePos;
+                int segOfs = s_binStreamSelectedOfs;
+                if (segOfs < 0)
+                    break;
+
+                int segSize = s_binStreamSelectedSize;
+                __syncthreads();
+
+                // Fetch triangles into the queue.
+
+                for (int idxInSeg = CR_COARSE_WARPS * 32 - 1 - thrInBlock; idxInSeg < segSize; idxInSeg += CR_COARSE_WARPS * 32)
+                {
+                    S32 triIdx = binSegData[segOfs + idxInSeg];
+                    s_triQueue[(triQueueWritePos - segSize + idxInSeg) & (CR_COARSE_QUEUE_SIZE - 1)] = triIdx;
+                }
+            }
+
+            // All threads: Clear emit masks.
+
+            for (int maskIdx = thrInBlock; maskIdx < CR_COARSE_WARPS * CR_BIN_SQR; maskIdx += CR_COARSE_WARPS * 32)
+                s_warpEmitMask[maskIdx >> (CR_BIN_LOG2 * 2)][maskIdx & (CR_BIN_SQR - 1)] = 0;
+
+            __syncthreads();
+
+            //------------------------------------------------------------------------
+            // Raster.
+            //------------------------------------------------------------------------
+
+            // Triangle per thread: Read from the queue.
+
+            int triIdx = -1;
+            if (triQueueReadPos + thrInBlock < triQueueWritePos)
+                triIdx = s_triQueue[(triQueueReadPos + thrInBlock) & (CR_COARSE_QUEUE_SIZE - 1)];
+
+            uint4 triData = make_uint4(0, 0, 0, 0);
+            if (triIdx != -1)
+            {
+                int dataIdx = triIdx >> 3;
+                int subtriIdx = triIdx & 7;
+                if (subtriIdx != 7)
+                    dataIdx = triHeader[dataIdx].misc + subtriIdx;
+                triData = *((uint4*)triHeader + dataIdx);
+            }
+
+            // 32 triangles per warp: Record emits (= tile intersections).
+
+            if (__any_sync(~0u, triIdx != -1))
+            {
+                S32 v0x = sub_s16lo_s16lo(triData.x, originX);
+                S32 v0y = sub_s16hi_s16lo(triData.x, originY);
+                S32 d01x = sub_s16lo_s16lo(triData.y, triData.x);
+                S32 d01y = sub_s16hi_s16hi(triData.y, triData.x);
+                S32 d02x = sub_s16lo_s16lo(triData.z, triData.x);
+                S32 d02y = sub_s16hi_s16hi(triData.z, triData.x);
+
+                // Compute tile-based AABB.
+
+                int lox = add_clamp_0_x((v0x + min_min(d01x, 0, d02x)) >> tileLog, 0, maxTileXInBin);
+                int loy = add_clamp_0_x((v0y + min_min(d01y, 0, d02y)) >> tileLog, 0, maxTileYInBin);
+                int hix = add_clamp_0_x((v0x + max_max(d01x, 0, d02x)) >> tileLog, 0, maxTileXInBin);
+                int hiy = add_clamp_0_x((v0y + max_max(d01y, 0, d02y)) >> tileLog, 0, maxTileYInBin);
+                int sizex = add_sub(hix, 1, lox);
+                int sizey = add_sub(hiy, 1, loy);
+                int area = sizex * sizey;
+
+                // Miscellaneous init.
+
+                U8* currPtr = (U8*)&s_warpEmitMask[threadIdx.y][lox + (loy << CR_BIN_LOG2)];
+                int ptrYInc = CR_BIN_SIZE * 4 - (sizex << 2);
+                U32 maskBit = 1 << threadIdx.x;
+
+                // Case A: All AABBs are small => record the full AABB using atomics.
+
+                if (__all_sync(~0u, sizex <= 2 && sizey <= 2))
+                {
+                    if (triIdx != -1)
+                    {
+                        atomicOr((U32*)currPtr, maskBit);
+                        if (sizex == 2) atomicOr((U32*)(currPtr + 4), maskBit);
+                        if (sizey == 2) atomicOr((U32*)(currPtr + CR_BIN_SIZE * 4), maskBit);
+                        if (sizex == 2 && sizey == 2) atomicOr((U32*)(currPtr + 4 + CR_BIN_SIZE * 4), maskBit);
+                    }
+                }
+                else
+                {
+                    // Compute warp-AABB (scan-32).
+
+                    U32 aabbMask = add_sub(2 << hix, 0x20000 << hiy, 1 << lox) - (0x10000 << loy);
+                    if (triIdx == -1)
+                        aabbMask = 0;
+
+                    volatile U32* v = &s_scanTemp[threadIdx.y][threadIdx.x + 16];
+                    v[0] = aabbMask; __syncwarp(); aabbMask |= v[-1]; __syncwarp();
+                    v[0] = aabbMask; __syncwarp(); aabbMask |= v[-2]; __syncwarp();
+                    v[0] = aabbMask; __syncwarp(); aabbMask |= v[-4]; __syncwarp();
+                    v[0] = aabbMask; __syncwarp(); aabbMask |= v[-8]; __syncwarp();
+                    v[0] = aabbMask; __syncwarp(); aabbMask |= v[-16]; __syncwarp();
+                    v[0] = aabbMask; __syncwarp(); aabbMask = s_scanTemp[threadIdx.y][47];
+
+                    U32 maskX = aabbMask & 0xFFFF;
+                    U32 maskY = aabbMask >> 16;
+                    int wlox = findLeadingOne(maskX ^ (maskX - 1));
+                    int wloy = findLeadingOne(maskY ^ (maskY - 1));
+                    int whix = findLeadingOne(maskX);
+                    int whiy = findLeadingOne(maskY);
+                    int warea = (add_sub(whix, 1, wlox)) * (add_sub(whiy, 1, wloy));
+
+                    // Initialize edge functions.
+
+                    S32 d12x = d02x - d01x;
+                    S32 d12y = d02y - d01y;
+                    v0x -= lox << tileLog;
+                    v0y -= loy << tileLog;
+
+                    S32 t01 = v0x * d01y - v0y * d01x;
+                    S32 t02 = v0y * d02x - v0x * d02y;
+                    S32 t12 = d01x * d12y - d01y * d12x - t01 - t02;
+                    S32 b01 = add_sub(t01 >> tileLog, ::max(d01x, 0), ::min(d01y, 0));
+                    S32 b02 = add_sub(t02 >> tileLog, ::max(d02y, 0), ::min(d02x, 0));
+                    S32 b12 = add_sub(t12 >> tileLog, ::max(d12x, 0), ::min(d12y, 0));
+
+                    d01x += sizex * d01y;
+                    d02x += sizex * d02y;
+                    d12x += sizex * d12y;
+
+                    // Case B: Warp-AABB is not much larger than largest AABB => Check tiles in warp-AABB, record using ballots.
+                    if (__any_sync(~0u, warea * 4 <= area * 8))
+                    {
+                        // Not sure if this is any faster than Case C after all the post-Volta ballot mask tracking.
+                        bool act = (triIdx != -1);
+                        U32 actMask = __ballot_sync(~0u, act);
+                        if (act)
+                        {
+                            for (int y = wloy; y <= whiy; y++)
+                            {
+                                bool yIn = (y >= loy && y <= hiy);
+                                U32 yMask = __ballot_sync(actMask, yIn);
+                                if (yIn)
+                                {
+                                    for (int x = wlox; x <= whix; x++)
+                                    {
+                                        bool xyIn = (x >= lox && x <= hix);
+                                        U32 xyMask = __ballot_sync(yMask, xyIn);
+                                        if (xyIn)
+                                        {
+                                            U32 res = __ballot_sync(xyMask, b01 >= 0 && b02 >= 0 && b12 >= 0);
+                                            if (threadIdx.x == 31 - __clz(xyMask))
+                                                *(U32*)currPtr = res;
+                                            currPtr += 4, b01 -= d01y, b02 += d02y, b12 -= d12y;
+                                        }
+                                    }
+                                    currPtr += ptrYInc, b01 += d01x, b02 -= d02x, b12 += d12x;
+                                }
+                            }
+                        }
+                    }
+
+                    // Case C: General case => Check tiles in AABB, record using atomics.
+
+                    else
+                    {
+                        if (triIdx != -1)
+                        {
+                            U8* skipPtr = currPtr + (sizex << 2);
+                            U8* endPtr  = currPtr + (sizey << (CR_BIN_LOG2 + 2));
+                            do
+                            {
+                                if (b01 >= 0 && b02 >= 0 && b12 >= 0)
+                                    atomicOr((U32*)currPtr, maskBit);
+                                currPtr += 4, b01 -= d01y, b02 += d02y, b12 -= d12y;
+                                if (currPtr == skipPtr)
+                                    currPtr += ptrYInc, b01 += d01x, b02 -= d02x, b12 += d12x, skipPtr += CR_BIN_SIZE * 4;
+                            }
+                            while (currPtr != endPtr);
+                        }
+                    }
+                }
+            }
+
+            __syncthreads();
+
+            //------------------------------------------------------------------------
+            // Count.
+            //------------------------------------------------------------------------
+
+            // Tile per thread: Initialize prefix sums.
+
+            for (int tileInBin_base = 0; tileInBin_base < CR_BIN_SQR; tileInBin_base += CR_COARSE_WARPS * 32)
+            {
+                int tileInBin = tileInBin_base + thrInBlock;
+                bool act = (tileInBin < CR_BIN_SQR);
+                U32 actMask = __ballot_sync(~0u, act);
+                if (act)
+                {
+                    // Compute prefix sum of emits over warps.
+
+                    U8* srcPtr = (U8*)&s_warpEmitMask[0][tileInBin];
+                    U8* dstPtr = (U8*)&s_warpEmitPrefixSum[0][tileInBin];
+                    int tileEmits = 0;
+                    for (int i = 0; i < CR_COARSE_WARPS; i++)
+                    {
+                        tileEmits += __popc(*(U32*)srcPtr);
+                        *(U32*)dstPtr = tileEmits;
+                        srcPtr += (CR_BIN_SQR + 1) * 4;
+                        dstPtr += (CR_BIN_SQR + 1) * 4;
+                    }
+
+                    // Determine the number of segments to allocate.
+
+                    int spaceLeft = -s_tileStreamCurrOfs[tileInBin] & (CR_TILE_SEG_SIZE - 1);
+                    int tileAllocs = (tileEmits - spaceLeft + CR_TILE_SEG_SIZE - 1) >> CR_TILE_SEG_LOG2;
+                    volatile U32* v = &s_tileEmitPrefixSum[tileInBin + 1];
+
+                    // All counters within the warp are small => compute prefix sum using ballot.
+
+                    if (!__any_sync(actMask, tileEmits >= 2))
+                    {
+                        U32 m = getLaneMaskLe();
+                        *v = (__popc(__ballot_sync(actMask, tileEmits & 1) & m) << emitShift) | __popc(__ballot_sync(actMask, tileAllocs & 1) & m);
+                    }
+
+                    // Otherwise => scan-32 within the warp.
+
+                    else
+                    {
+                        U32 sum = (tileEmits << emitShift) | tileAllocs;
+                        *v = sum; __syncwarp(actMask); if (threadIdx.x >= 1)  sum += v[-1]; __syncwarp(actMask);
+                        *v = sum; __syncwarp(actMask); if (threadIdx.x >= 2)  sum += v[-2]; __syncwarp(actMask);
+                        *v = sum; __syncwarp(actMask); if (threadIdx.x >= 4)  sum += v[-4]; __syncwarp(actMask);
+                        *v = sum; __syncwarp(actMask); if (threadIdx.x >= 8)  sum += v[-8]; __syncwarp(actMask);
+                        *v = sum; __syncwarp(actMask); if (threadIdx.x >= 16) sum += v[-16]; __syncwarp(actMask);
+                        *v = sum; __syncwarp(actMask);
+                    }
+                }
+            }
+
+            // First warp: Scan-8.
+
+            __syncthreads();
+
+            bool scan8 = (thrInBlock < CR_BIN_SQR / 32);
+            U32 scan8Mask = __ballot_sync(~0u, scan8);
+            if (scan8)
+            {
+                int sum = s_tileEmitPrefixSum[(thrInBlock << 5) + 32];
+                volatile U32* v = &s_scanTemp[0][thrInBlock + 16];
+                v[0] = sum; __syncwarp(scan8Mask);
+                #if (CR_BIN_SQR > 1 * 32)
+                    sum += v[-1]; __syncwarp(scan8Mask); v[0] = sum; __syncwarp(scan8Mask);
+                #endif
+                #if (CR_BIN_SQR > 2 * 32)
+                    sum += v[-2]; __syncwarp(scan8Mask); v[0] = sum; __syncwarp(scan8Mask);
+                #endif
+                #if (CR_BIN_SQR > 4 * 32)
+                    sum += v[-4]; __syncwarp(scan8Mask); v[0] = sum; __syncwarp(scan8Mask);
+                #endif
+            }
+
+            __syncthreads();
+
+            // Tile per thread: Finalize prefix sums.
+            // Single thread: Allocate segments.
+
+            for (int tileInBin = thrInBlock; tileInBin < CR_BIN_SQR; tileInBin += CR_COARSE_WARPS * 32)
+            {
+                int sum = s_tileEmitPrefixSum[tileInBin + 1] + s_scanTemp[0][(tileInBin >> 5) + 15];
+                int numEmits = sum >> emitShift;
+                int numAllocs = sum & ((1 << emitShift) - 1);
+                s_tileEmitPrefixSum[tileInBin + 1] = numEmits;
+                s_tileAllocPrefixSum[tileInBin + 1] = numAllocs;
+
+                if (tileInBin == CR_BIN_SQR - 1 && numAllocs != 0)
+                {
+                    int t = atomicAdd(&atomics.numTileSegs, numAllocs);
+                    s_firstAllocSeg = (t + numAllocs <= p.maxTileSegs) ? t : 0;
+                }
+            }
+
+            __syncthreads();
+            int firstAllocSeg   = s_firstAllocSeg;
+            int totalEmits      = s_tileEmitPrefixSum[CR_BIN_SQR];
+            int totalAllocs     = s_tileAllocPrefixSum[CR_BIN_SQR];
+
+            //------------------------------------------------------------------------
+            // Emit.
+            //------------------------------------------------------------------------
+
+            // Emit per thread: Write triangle index to globalmem.
+
+            for (int emitInBin = thrInBlock; emitInBin < totalEmits; emitInBin += CR_COARSE_WARPS * 32)
+            {
+                // Find tile in bin.
+
+                U8* tileBase = (U8*)&s_tileEmitPrefixSum[0];
+                U8* tilePtr = tileBase;
+                U8* ptr;
+
+                #if (CR_BIN_SQR > 128)
+                    ptr = tilePtr + 0x80 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+                #if (CR_BIN_SQR > 64)
+                    ptr = tilePtr + 0x40 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+                #if (CR_BIN_SQR > 32)
+                    ptr = tilePtr + 0x20 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+                #if (CR_BIN_SQR > 16)
+                    ptr = tilePtr + 0x10 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+                #if (CR_BIN_SQR > 8)
+                    ptr = tilePtr + 0x08 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+                #if (CR_BIN_SQR > 4)
+                    ptr = tilePtr + 0x04 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+                #if (CR_BIN_SQR > 2)
+                    ptr = tilePtr + 0x02 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+                #if (CR_BIN_SQR > 1)
+                    ptr = tilePtr + 0x01 * 4; if (emitInBin >= *(U32*)ptr) tilePtr = ptr;
+                #endif
+
+                int tileInBin = (tilePtr - tileBase) >> 2;
+                int emitInTile = emitInBin - *(U32*)tilePtr;
+
+                // Find warp in tile.
+
+                int warpStep = (CR_BIN_SQR + 1) * 4;
+                U8* warpBase = (U8*)&s_warpEmitPrefixSum[0][tileInBin] - warpStep;
+                U8* warpPtr = warpBase;
+
+                #if (CR_COARSE_WARPS > 8)
+                    ptr = warpPtr + 0x08 * warpStep; if (emitInTile >= *(U32*)ptr) warpPtr = ptr;
+                #endif
+                #if (CR_COARSE_WARPS > 4)
+                    ptr = warpPtr + 0x04 * warpStep; if (emitInTile >= *(U32*)ptr) warpPtr = ptr;
+                #endif
+                #if (CR_COARSE_WARPS > 2)
+                    ptr = warpPtr + 0x02 * warpStep; if (emitInTile >= *(U32*)ptr) warpPtr = ptr;
+                #endif
+                #if (CR_COARSE_WARPS > 1)
+                    ptr = warpPtr + 0x01 * warpStep; if (emitInTile >= *(U32*)ptr) warpPtr = ptr;
+                #endif
+
+                int warpInTile = (warpPtr - warpBase) >> (CR_BIN_LOG2 * 2 + 2);
+                U32 emitMask = *(U32*)(warpPtr + warpStep + ((U8*)s_warpEmitMask - (U8*)s_warpEmitPrefixSum));
+                int emitInWarp = emitInTile - *(U32*)(warpPtr + warpStep) + __popc(emitMask);
+
+                // Find thread in warp.
+
+                int threadInWarp = 0;
+                int pop = __popc(emitMask & 0xFFFF);
+                bool pred = (emitInWarp >= pop);
+                if (pred) emitInWarp -= pop;
+                if (pred) emitMask >>= 0x10;
+                if (pred) threadInWarp += 0x10;
+
+                pop = __popc(emitMask & 0xFF);
+                pred = (emitInWarp >= pop);
+                if (pred) emitInWarp -= pop;
+                if (pred) emitMask >>= 0x08;
+                if (pred) threadInWarp += 0x08;
+
+                pop = __popc(emitMask & 0xF);
+                pred = (emitInWarp >= pop);
+                if (pred) emitInWarp -= pop;
+                if (pred) emitMask >>= 0x04;
+                if (pred) threadInWarp += 0x04;
+
+                pop = __popc(emitMask & 0x3);
+                pred = (emitInWarp >= pop);
+                if (pred) emitInWarp -= pop;
+                if (pred) emitMask >>= 0x02;
+                if (pred) threadInWarp += 0x02;
+
+                if (emitInWarp >= (emitMask & 1))
+                    threadInWarp++;
+
+                // Figure out where to write.
+
+                int currOfs = s_tileStreamCurrOfs[tileInBin];
+                int spaceLeft = -currOfs & (CR_TILE_SEG_SIZE - 1);
+                int outOfs = emitInTile;
+
+                if (outOfs < spaceLeft)
+                    outOfs += currOfs;
+                else
+                {
+                    int allocLo = firstAllocSeg + s_tileAllocPrefixSum[tileInBin];
+                    outOfs += (allocLo << CR_TILE_SEG_LOG2) - spaceLeft;
+                }
+
+                // Write.
+
+                int queueIdx = warpInTile * 32 + threadInWarp;
+                int triIdx = s_triQueue[(triQueueReadPos + queueIdx) & (CR_COARSE_QUEUE_SIZE - 1)];
+
+                tileSegData[outOfs] = triIdx;
+            }
+
+            //------------------------------------------------------------------------
+            // Patch.
+            //------------------------------------------------------------------------
+
+            // Allocated segment per thread: Initialize next-pointer and count.
+
+            for (int i = CR_COARSE_WARPS * 32 - 1 - thrInBlock; i < totalAllocs; i += CR_COARSE_WARPS * 32)
+            {
+                int segIdx = firstAllocSeg + i;
+                tileSegNext[segIdx] = segIdx + 1;
+                tileSegCount[segIdx] = CR_TILE_SEG_SIZE;
+            }
+
+            // Tile per thread: Fix previous segment's next-pointer and update s_tileStreamCurrOfs.
+
+            __syncthreads();
+            for (int tileInBin = CR_COARSE_WARPS * 32 - 1 - thrInBlock; tileInBin < CR_BIN_SQR; tileInBin += CR_COARSE_WARPS * 32)
+            {
+                int oldOfs = s_tileStreamCurrOfs[tileInBin];
+                int newOfs = oldOfs + s_warpEmitPrefixSum[CR_COARSE_WARPS - 1][tileInBin];
+                int allocLo = s_tileAllocPrefixSum[tileInBin];
+                int allocHi = s_tileAllocPrefixSum[tileInBin + 1];
+
+                if (allocLo != allocHi)
+                {
+                    S32* nextPtr = &tileSegNext[(oldOfs - 1) >> CR_TILE_SEG_LOG2];
+                    if (oldOfs < 0)
+                        nextPtr = &tileFirstSeg[binTileIdx + globalTileIdx(tileInBin, p.widthTiles)];
+                    *nextPtr = firstAllocSeg + allocLo;
+
+                    newOfs--;
+                    newOfs &= CR_TILE_SEG_SIZE - 1;
+                    newOfs |= (firstAllocSeg + allocHi - 1) << CR_TILE_SEG_LOG2;
+                    newOfs++;
+                }
+                s_tileStreamCurrOfs[tileInBin] = newOfs;
+            }
+
+            // Advance queue read pointer.
+            // Queue became empty => bin done.
+
+            triQueueReadPos += CR_COARSE_WARPS * 32;
+        }
+        while (triQueueReadPos < triQueueWritePos);
+
+        // Tile per thread: Fix next-pointer and count of the last segment.
+        // 32 tiles per warp: Count active tiles.
+
+        __syncthreads();
+
+        for (int tileInBin_base = 0; tileInBin_base < CR_BIN_SQR; tileInBin_base += CR_COARSE_WARPS * 32)
+        {
+            int tileInBin = tileInBin_base + thrInBlock;
+            bool act = (tileInBin < CR_BIN_SQR);
+            U32 actMask = __ballot_sync(~0u, act);
+            if (act)
+            {
+                int tileX = tileInBin & (CR_BIN_SIZE - 1);
+                int tileY = tileInBin >> CR_BIN_LOG2;
+                bool force = (p.deferredClear & tileX <= maxTileXInBin & tileY <= maxTileYInBin);
+
+                int ofs = s_tileStreamCurrOfs[tileInBin];
+                int segIdx = (ofs - 1) >> CR_TILE_SEG_LOG2;
+                int segCount = ofs & (CR_TILE_SEG_SIZE - 1);
+
+                if (ofs >= 0)
+                    tileSegNext[segIdx] = -1;
+                else if (force)
+                {
+                    s_tileStreamCurrOfs[tileInBin] = 0;
+                    tileFirstSeg[binTileIdx + tileX + tileY * p.widthTiles] = -1;
+                }
+
+                if (segCount != 0)
+                    tileSegCount[segIdx] = segCount;
+
+                U32 res = __ballot_sync(actMask, ofs >= 0 | force);
+                if (threadIdx.x == 0)
+                    s_scanTemp[0][(tileInBin >> 5) + 16] = __popc(res);
+            }
+        }
+
+        // First warp: Scan-8.
+        // One thread: Allocate space for active tiles.
+
+        __syncthreads();
+
+        bool scan8 = (thrInBlock < CR_BIN_SQR / 32);
+        U32 scan8Mask = __ballot_sync(~0u, scan8);
+        if (scan8)
+        {
+            volatile U32* v = &s_scanTemp[0][thrInBlock + 16];
+            U32 sum = v[0];
+            #if (CR_BIN_SQR > 1 * 32)
+                sum += v[-1]; __syncwarp(scan8Mask); v[0] = sum; __syncwarp(scan8Mask);
+            #endif
+            #if (CR_BIN_SQR > 2 * 32)
+                sum += v[-2]; __syncwarp(scan8Mask); v[0] = sum; __syncwarp(scan8Mask);
+            #endif
+            #if (CR_BIN_SQR > 4 * 32)
+                sum += v[-4]; __syncwarp(scan8Mask); v[0] = sum; __syncwarp(scan8Mask);
+            #endif
+
+            if (thrInBlock == CR_BIN_SQR / 32 - 1)
+                s_firstActiveIdx = atomicAdd(&atomics.numActiveTiles, sum);
+        }
+
+        // Tile per thread: Output active tiles.
+
+        __syncthreads();
+
+        for (int tileInBin_base = 0; tileInBin_base < CR_BIN_SQR; tileInBin_base += CR_COARSE_WARPS * 32)
+        {
+            int tileInBin = tileInBin_base + thrInBlock;
+            bool act = (tileInBin < CR_BIN_SQR) && (s_tileStreamCurrOfs[tileInBin] >= 0);
+            U32 actMask = __ballot_sync(~0u, act);
+            if (act)
+            {
+                int activeIdx = s_firstActiveIdx;
+                activeIdx += s_scanTemp[0][(tileInBin >> 5) + 15];
+                activeIdx += __popc(actMask & getLaneMaskLt());
+                activeTiles[activeIdx] = binTileIdx + globalTileIdx(tileInBin, p.widthTiles);
+            }
+        }
+    }
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Constants.hpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Constants.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..916315cdec21948632ce8b3b383ee654225aad9c
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Constants.hpp
@@ -0,0 +1,73 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+
+//------------------------------------------------------------------------
+
+#define CR_MAXVIEWPORT_LOG2     11      // ViewportSize / PixelSize.
+#define CR_SUBPIXEL_LOG2        4       // PixelSize / SubpixelSize.
+
+#define CR_MAXBINS_LOG2         4       // ViewportSize / BinSize.
+#define CR_BIN_LOG2             4       // BinSize / TileSize.
+#define CR_TILE_LOG2            3       // TileSize / PixelSize.
+
+#define CR_COVER8X8_LUT_SIZE    768     // 64-bit entries.
+#define CR_FLIPBIT_FLIP_Y       2
+#define CR_FLIPBIT_FLIP_X       3
+#define CR_FLIPBIT_SWAP_XY      4
+#define CR_FLIPBIT_COMPL        5
+
+#define CR_BIN_STREAMS_LOG2     4
+#define CR_BIN_SEG_LOG2         9       // 32-bit entries.
+#define CR_TILE_SEG_LOG2        5       // 32-bit entries.
+
+#define CR_MAXSUBTRIS_LOG2      24      // Triangle structs. Dictated by CoarseRaster.
+#define CR_COARSE_QUEUE_LOG2    10      // Triangles.
+
+#define CR_SETUP_WARPS          2
+#define CR_SETUP_OPT_BLOCKS     8
+#define CR_BIN_WARPS            16
+#define CR_COARSE_WARPS         16      // Must be a power of two.
+#define CR_FINE_MAX_WARPS       20
+
+#define CR_EMBED_IMAGE_PARAMS   32      // Number of per-image parameter structs embedded in kernel launch parameter block.
+
+//------------------------------------------------------------------------
+
+#define CR_MAXVIEWPORT_SIZE     (1 << CR_MAXVIEWPORT_LOG2)
+#define CR_SUBPIXEL_SIZE        (1 << CR_SUBPIXEL_LOG2)
+#define CR_SUBPIXEL_SQR         (1 << (CR_SUBPIXEL_LOG2 * 2))
+
+#define CR_MAXBINS_SIZE         (1 << CR_MAXBINS_LOG2)
+#define CR_MAXBINS_SQR          (1 << (CR_MAXBINS_LOG2 * 2))
+#define CR_BIN_SIZE             (1 << CR_BIN_LOG2)
+#define CR_BIN_SQR              (1 << (CR_BIN_LOG2 * 2))
+
+#define CR_MAXTILES_LOG2        (CR_MAXBINS_LOG2 + CR_BIN_LOG2)
+#define CR_MAXTILES_SIZE        (1 << CR_MAXTILES_LOG2)
+#define CR_MAXTILES_SQR         (1 << (CR_MAXTILES_LOG2 * 2))
+#define CR_TILE_SIZE            (1 << CR_TILE_LOG2)
+#define CR_TILE_SQR             (1 << (CR_TILE_LOG2 * 2))
+
+#define CR_BIN_STREAMS_SIZE     (1 << CR_BIN_STREAMS_LOG2)
+#define CR_BIN_SEG_SIZE         (1 << CR_BIN_SEG_LOG2)
+#define CR_TILE_SEG_SIZE        (1 << CR_TILE_SEG_LOG2)
+
+#define CR_MAXSUBTRIS_SIZE      (1 << CR_MAXSUBTRIS_LOG2)
+#define CR_COARSE_QUEUE_SIZE    (1 << CR_COARSE_QUEUE_LOG2)
+
+//------------------------------------------------------------------------
+// When evaluating interpolated Z pixel centers, we may introduce an error
+// of (+-CR_LERP_ERROR) ULPs.
+
+#define CR_LERP_ERROR(SAMPLES_LOG2) (2200u << (SAMPLES_LOG2))
+#define CR_DEPTH_MIN                CR_LERP_ERROR(3)
+#define CR_DEPTH_MAX                (CR_U32_MAX - CR_LERP_ERROR(3))
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/CudaRaster.cpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/CudaRaster.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..db8bf31434bf2ac1ba420e9aa0fc3a14c05f5c73
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/CudaRaster.cpp
@@ -0,0 +1,79 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "Defs.hpp"
+#include "../CudaRaster.hpp"
+#include "RasterImpl.hpp"
+
+using namespace CR;
+
+//------------------------------------------------------------------------
+// Stub interface implementation.
+//------------------------------------------------------------------------
+
+CudaRaster::CudaRaster()
+{
+    m_impl = new RasterImpl();
+}
+
+CudaRaster::~CudaRaster()
+{
+    delete m_impl;
+}
+
+void CudaRaster::setBufferSize(int width, int height, int numImages)
+{
+    m_impl->setBufferSize(Vec3i(width, height, numImages));
+}
+
+void CudaRaster::setViewport(int width, int height, int offsetX, int offsetY)
+{
+    m_impl->setViewport(Vec2i(width, height), Vec2i(offsetX, offsetY));
+}
+
+void CudaRaster::setRenderModeFlags(U32 flags)
+{
+    m_impl->setRenderModeFlags(flags);
+}
+
+void CudaRaster::deferredClear(U32 clearColor)
+{
+    m_impl->deferredClear(clearColor);
+}
+
+void CudaRaster::setVertexBuffer(void* vertices, int numVertices)
+{
+    m_impl->setVertexBuffer(vertices, numVertices);
+}
+
+void CudaRaster::setIndexBuffer(void* indices, int numTriangles)
+{
+    m_impl->setIndexBuffer(indices, numTriangles);
+}
+
+bool CudaRaster::drawTriangles(const int* ranges, bool peel, cudaStream_t stream)
+{
+    return m_impl->drawTriangles((const Vec2i*)ranges, peel, stream);
+}
+
+void* CudaRaster::getColorBuffer(void)
+{
+    return m_impl->getColorBuffer();
+}
+
+void* CudaRaster::getDepthBuffer(void)
+{
+    return m_impl->getDepthBuffer();
+}
+
+void CudaRaster::swapDepthAndPeel(void)
+{
+    m_impl->swapDepthAndPeel();
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Defs.hpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Defs.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..7aa7774c652954dc975b48f1f6f839369d191e4c
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Defs.hpp
@@ -0,0 +1,90 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include <cuda_runtime.h>
+#include <cstdint>
+
+namespace CR
+{
+//------------------------------------------------------------------------
+
+#ifndef NULL
+#   define NULL 0
+#endif
+
+#ifdef __CUDACC__
+#   define CR_CUDA 1
+#else
+#   define CR_CUDA 0
+#endif
+
+#if CR_CUDA
+#   define CR_CUDA_FUNC     __device__ __inline__
+#   define CR_CUDA_CONST    __constant__
+#else
+#   define CR_CUDA_FUNC     inline
+#   define CR_CUDA_CONST    static const
+#endif
+
+#define CR_UNREF(X)         ((void)(X))
+#define CR_ARRAY_SIZE(X)    ((int)(sizeof(X) / sizeof((X)[0])))
+
+//------------------------------------------------------------------------
+
+typedef uint8_t             U8;
+typedef uint16_t            U16;
+typedef uint32_t            U32;
+typedef uint64_t            U64;
+typedef int8_t              S8;
+typedef int16_t             S16;
+typedef int32_t             S32;
+typedef int64_t             S64;
+typedef float               F32;
+typedef double              F64;
+typedef void                (*FuncPtr)(void);
+
+//------------------------------------------------------------------------
+
+#define CR_U32_MAX          (0xFFFFFFFFu)
+#define CR_S32_MIN          (~0x7FFFFFFF)
+#define CR_S32_MAX          (0x7FFFFFFF)
+#define CR_U64_MAX          ((U64)(S64)-1)
+#define CR_S64_MIN          ((S64)-1 << 63)
+#define CR_S64_MAX          (~((S64)-1 << 63))
+#define CR_F32_MIN          (1.175494351e-38f)
+#define CR_F32_MAX          (3.402823466e+38f)
+#define CR_F64_MIN          (2.2250738585072014e-308)
+#define CR_F64_MAX          (1.7976931348623158e+308)
+
+//------------------------------------------------------------------------
+// Misc types.
+
+class Vec2i
+{
+public:
+    Vec2i(int x_, int y_) : x(x_), y(y_) {}
+    int x, y;
+};
+
+class Vec3i
+{
+public:
+    Vec3i(int x_, int y_, int z_) : x(x_), y(y_), z(z_) {}
+    int x, y, z;
+};
+
+//------------------------------------------------------------------------
+// CUDA utilities.
+
+#if CR_CUDA
+#   define globalThreadIdx (threadIdx.x + blockDim.x * (threadIdx.y + blockDim.y * (blockIdx.x + gridDim.x * blockIdx.y)))
+#endif
+
+//------------------------------------------------------------------------
+} // namespace CR
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/FineRaster.inl b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/FineRaster.inl
new file mode 100644
index 0000000000000000000000000000000000000000..720e9997cf04265a6e1a28f8f0cd2d7b34a25e28
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/FineRaster.inl
@@ -0,0 +1,385 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+// Utility funcs.
+//------------------------------------------------------------------------
+
+__device__ __inline__ void initTileZMax(U32& tileZMax, bool& tileZUpd, volatile U32* tileDepth)
+{
+    tileZMax = CR_DEPTH_MAX;
+    tileZUpd = (::min(tileDepth[threadIdx.x], tileDepth[threadIdx.x + 32]) < tileZMax);
+}
+
+__device__ __inline__ void updateTileZMax(U32& tileZMax, bool& tileZUpd, volatile U32* tileDepth, volatile U32* temp)
+{
+    // Entry is warp-coherent.
+    if (__any_sync(~0u, tileZUpd))
+    {
+        U32 z = ::max(tileDepth[threadIdx.x], tileDepth[threadIdx.x + 32]); __syncwarp();
+        temp[threadIdx.x + 16] = z; __syncwarp();
+        z = ::max(z, temp[threadIdx.x + 16 -  1]); __syncwarp(); temp[threadIdx.x + 16] = z; __syncwarp();
+        z = ::max(z, temp[threadIdx.x + 16 -  2]); __syncwarp(); temp[threadIdx.x + 16] = z; __syncwarp();
+        z = ::max(z, temp[threadIdx.x + 16 -  4]); __syncwarp(); temp[threadIdx.x + 16] = z; __syncwarp();
+        z = ::max(z, temp[threadIdx.x + 16 -  8]); __syncwarp(); temp[threadIdx.x + 16] = z; __syncwarp();
+        z = ::max(z, temp[threadIdx.x + 16 - 16]); __syncwarp(); temp[threadIdx.x + 16] = z; __syncwarp();
+        tileZMax = temp[47];
+        tileZUpd = false;
+    }
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void getTriangle(const CRParams& p, S32& triIdx, S32& dataIdx, uint4& triHeader, S32& segment)
+{
+    const CRTriangleHeader* triHeaderPtr    = (const CRTriangleHeader*)p.triHeader + blockIdx.z * p.maxSubtris;;
+    const S32*              tileSegData     = (const S32*)p.tileSegData  + p.maxTileSegs * CR_TILE_SEG_SIZE * blockIdx.z;
+    const S32*              tileSegNext     = (const S32*)p.tileSegNext  + p.maxTileSegs * blockIdx.z;
+    const S32*              tileSegCount    = (const S32*)p.tileSegCount + p.maxTileSegs * blockIdx.z;
+
+    if (threadIdx.x >= tileSegCount[segment])
+    {
+        triIdx = -1;
+        dataIdx = -1;
+    }
+    else
+    {
+        int subtriIdx = tileSegData[segment * CR_TILE_SEG_SIZE + threadIdx.x];
+        triIdx = subtriIdx >> 3;
+        dataIdx = triIdx;
+        subtriIdx &= 7;
+        if (subtriIdx != 7)
+            dataIdx = triHeaderPtr[triIdx].misc + subtriIdx;
+        triHeader = *((uint4*)triHeaderPtr + dataIdx);
+    }
+
+    // advance to next segment
+    segment = tileSegNext[segment];
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ bool earlyZCull(uint4 triHeader, U32 tileZMax)
+{
+    U32 zmin = triHeader.w & 0xFFFFF000;
+    return (zmin > tileZMax);
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U64 trianglePixelCoverage(const CRParams& p, const uint4& triHeader, int tileX, int tileY, volatile U64* s_cover8x8_lut)
+{
+    int baseX = (tileX << (CR_TILE_LOG2 + CR_SUBPIXEL_LOG2)) - ((p.widthPixelsVp  - 1) << (CR_SUBPIXEL_LOG2 - 1));
+    int baseY = (tileY << (CR_TILE_LOG2 + CR_SUBPIXEL_LOG2)) - ((p.heightPixelsVp - 1) << (CR_SUBPIXEL_LOG2 - 1));
+
+    // extract S16 vertex positions while subtracting tile coordinates
+    S32 v0x  = sub_s16lo_s16lo(triHeader.x, baseX);
+    S32 v0y  = sub_s16hi_s16lo(triHeader.x, baseY);
+    S32 v01x = sub_s16lo_s16lo(triHeader.y, triHeader.x);
+    S32 v01y = sub_s16hi_s16hi(triHeader.y, triHeader.x);
+    S32 v20x = sub_s16lo_s16lo(triHeader.x, triHeader.z);
+    S32 v20y = sub_s16hi_s16hi(triHeader.x, triHeader.z);
+
+    // extract flipbits
+    U32 f01 = (triHeader.w >> 6) & 0x3C;
+    U32 f12 = (triHeader.w >> 2) & 0x3C;
+    U32 f20 = (triHeader.w << 2) & 0x3C;
+
+    // compute per-edge coverage masks
+    U64 c01, c12, c20;
+    c01 = cover8x8_exact_fast(v0x, v0y, v01x, v01y, f01, s_cover8x8_lut);
+    c12 = cover8x8_exact_fast(v0x + v01x, v0y + v01y, -v01x - v20x, -v01y - v20y, f12, s_cover8x8_lut);
+    c20 = cover8x8_exact_fast(v0x, v0y, v20x, v20y, f20, s_cover8x8_lut);
+
+    // combine masks
+    return c01 & c12 & c20;
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U32 scan32_value(U32 value, volatile U32* temp)
+{
+    __syncwarp();
+    temp[threadIdx.x + 16] = value; __syncwarp();
+    value += temp[threadIdx.x + 16 -  1]; __syncwarp(); temp[threadIdx.x + 16] = value; __syncwarp();
+    value += temp[threadIdx.x + 16 -  2]; __syncwarp(); temp[threadIdx.x + 16] = value; __syncwarp();
+    value += temp[threadIdx.x + 16 -  4]; __syncwarp(); temp[threadIdx.x + 16] = value; __syncwarp();
+    value += temp[threadIdx.x + 16 -  8]; __syncwarp(); temp[threadIdx.x + 16] = value; __syncwarp();
+    value += temp[threadIdx.x + 16 - 16]; __syncwarp(); temp[threadIdx.x + 16] = value; __syncwarp();
+    return value;
+}
+
+__device__ __inline__ volatile const U32& scan32_total(volatile U32* temp)
+{
+    return temp[47];
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ S32 findBit(U64 mask, int idx)
+{
+    U32 x = getLo(mask);
+    int  pop = __popc(x);
+    bool p   = (pop <= idx);
+    if (p) x = getHi(mask);
+    if (p) idx -= pop;
+    int bit = p ? 32 : 0;
+
+    pop = __popc(x & 0x0000ffffu);
+    p   = (pop <= idx);
+    if (p) x >>= 16;
+    if (p) bit += 16;
+    if (p) idx -= pop;
+
+    U32 tmp = x & 0x000000ffu;
+    pop = __popc(tmp);
+    p   = (pop <= idx);
+    if (p) tmp = x & 0x0000ff00u;
+    if (p) idx -= pop;
+
+    return findLeadingOne(tmp) + bit - idx;
+}
+
+//------------------------------------------------------------------------
+// Single-sample implementation.
+//------------------------------------------------------------------------
+
+__device__ __inline__ void executeROP(U32 color, U32 depth, volatile U32* pColor, volatile U32* pDepth, U32 ropMask)
+{
+    atomicMin((U32*)pDepth, depth);
+    __syncwarp(ropMask);
+    bool act = (depth == *pDepth);
+    __syncwarp(ropMask);
+    U32 actMask = __ballot_sync(ropMask, act);
+    if (act)
+    {
+        *pDepth = 0;
+        __syncwarp(actMask);
+        atomicMax((U32*)pDepth, threadIdx.x);
+        __syncwarp(actMask);
+        if (*pDepth == threadIdx.x)
+        {
+            *pDepth = depth;
+            *pColor = color;
+        }
+        __syncwarp(actMask);
+    }
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void fineRasterImpl(const CRParams p)
+{
+                                                                            // for 20 warps:
+    __shared__ volatile U64 s_cover8x8_lut[CR_COVER8X8_LUT_SIZE];           // 6KB
+    __shared__ volatile U32 s_tileColor   [CR_FINE_MAX_WARPS][CR_TILE_SQR]; // 5KB
+    __shared__ volatile U32 s_tileDepth   [CR_FINE_MAX_WARPS][CR_TILE_SQR]; // 5KB
+    __shared__ volatile U32 s_tilePeel    [CR_FINE_MAX_WARPS][CR_TILE_SQR]; // 5KB
+    __shared__ volatile U32 s_triDataIdx  [CR_FINE_MAX_WARPS][64];          // 5KB  CRTriangleData index
+    __shared__ volatile U64 s_triangleCov [CR_FINE_MAX_WARPS][64];          // 10KB coverage mask
+    __shared__ volatile U32 s_triangleFrag[CR_FINE_MAX_WARPS][64];          // 5KB  fragment index
+    __shared__ volatile U32 s_temp        [CR_FINE_MAX_WARPS][80];          // 6.25KB
+                                                                            // = 47.25KB total
+
+    CRAtomics&            atomics   = p.atomics[blockIdx.z];
+    const CRTriangleData* triData   = (const CRTriangleData*)p.triData + blockIdx.z * p.maxSubtris;
+
+    const S32*      activeTiles     = (const S32*)p.activeTiles  + CR_MAXTILES_SQR * blockIdx.z;
+    const S32*      tileFirstSeg    = (const S32*)p.tileFirstSeg + CR_MAXTILES_SQR * blockIdx.z;
+
+    volatile U32*   tileColor       = s_tileColor[threadIdx.y];
+    volatile U32*   tileDepth       = s_tileDepth[threadIdx.y];
+    volatile U32*   tilePeel        = s_tilePeel[threadIdx.y];
+    volatile U32*   triDataIdx      = s_triDataIdx[threadIdx.y];
+    volatile U64*   triangleCov     = s_triangleCov[threadIdx.y];
+    volatile U32*   triangleFrag    = s_triangleFrag[threadIdx.y];
+    volatile U32*   temp            = s_temp[threadIdx.y];
+
+    if (atomics.numSubtris > p.maxSubtris || atomics.numBinSegs > p.maxBinSegs || atomics.numTileSegs > p.maxTileSegs)
+        return;
+
+    temp[threadIdx.x] = 0; // first 16 elements of temp are always zero
+    cover8x8_setupLUT(s_cover8x8_lut);
+    __syncthreads();
+
+    // loop over tiles
+    for (;;)
+    {
+        // pick a tile
+        if (threadIdx.x == 0)
+            temp[16] = atomicAdd(&atomics.fineCounter, 1);
+        __syncwarp();
+        int activeIdx = temp[16];
+        if (activeIdx >= atomics.numActiveTiles)
+            break;
+
+        int tileIdx = activeTiles[activeIdx];
+        S32 segment = tileFirstSeg[tileIdx];
+        int tileY = tileIdx / p.widthTiles;
+        int tileX = tileIdx - tileY * p.widthTiles;
+        int px = (tileX << CR_TILE_LOG2) + (threadIdx.x & (CR_TILE_SIZE - 1));
+        int py = (tileY << CR_TILE_LOG2) + (threadIdx.x >> CR_TILE_LOG2);
+
+        // initialize per-tile state
+        int triRead = 0, triWrite = 0;
+        int fragRead = 0, fragWrite = 0;
+        if (threadIdx.x == 0)
+            triangleFrag[63] = 0; // "previous triangle"
+
+        // deferred clear => clear tile
+        if (p.deferredClear)
+        {
+			tileColor[threadIdx.x] = p.clearColor;
+            tileDepth[threadIdx.x] = p.clearDepth;
+            tileColor[threadIdx.x + 32] = p.clearColor;
+            tileDepth[threadIdx.x + 32] = p.clearDepth;
+        }
+        else // otherwise => read tile from framebuffer
+        {
+            U32* pColor = (U32*)p.colorBuffer + p.strideX * p.strideY * blockIdx.z;
+            U32* pDepth = (U32*)p.depthBuffer + p.strideX * p.strideY * blockIdx.z;
+			tileColor[threadIdx.x] = pColor[px + p.strideX * py];
+            tileDepth[threadIdx.x] = pDepth[px + p.strideX * py];
+            tileColor[threadIdx.x + 32] = pColor[px + p.strideX * (py + 4)];
+            tileDepth[threadIdx.x + 32] = pDepth[px + p.strideX * (py + 4)];
+        }
+
+        // read peeling inputs if enabled
+        if (p.renderModeFlags & CudaRaster::RenderModeFlag_EnableDepthPeeling)
+        {
+            U32* pPeel = (U32*)p.peelBuffer + p.strideX * p.strideY * blockIdx.z;
+            tilePeel[threadIdx.x] = pPeel[px + p.strideX * py];
+            tilePeel[threadIdx.x + 32] = pPeel[px + p.strideX * (py + 4)];
+        }
+
+        U32 tileZMax;
+        bool tileZUpd;
+        initTileZMax(tileZMax, tileZUpd, tileDepth);
+
+        // process fragments
+        for(;;)
+        {
+            // need to queue more fragments?
+            if (fragWrite - fragRead < 32 && segment >= 0)
+            {
+                // update tile z - coherent over warp
+                updateTileZMax(tileZMax, tileZUpd, tileDepth, temp);
+
+                // read triangles
+                do
+                {
+                    // read triangle index and data, advance to next segment
+                    S32 triIdx, dataIdx;
+                    uint4 triHeader;
+                    getTriangle(p, triIdx, dataIdx, triHeader, segment);
+
+                    // early z cull
+                    if (triIdx >= 0 && earlyZCull(triHeader, tileZMax))
+                        triIdx = -1;
+
+                    // determine coverage
+                    U64 coverage = trianglePixelCoverage(p, triHeader, tileX, tileY, s_cover8x8_lut);
+                    S32 pop = (triIdx == -1) ? 0 : __popcll(coverage);
+
+                    // fragment count scan
+                    U32 frag = scan32_value(pop, temp);
+                    frag += fragWrite; // frag now holds cumulative fragment count
+                    fragWrite += scan32_total(temp);
+
+                    // queue non-empty triangles
+                    U32 goodMask = __ballot_sync(~0u, pop != 0);
+                    if (pop != 0)
+                    {
+                        int idx = (triWrite + __popc(goodMask & getLaneMaskLt())) & 63;
+                        triDataIdx  [idx] = dataIdx;
+                        triangleFrag[idx] = frag;
+                        triangleCov [idx] = coverage;
+                    }
+                    triWrite += __popc(goodMask);
+                }
+                while (fragWrite - fragRead < 32 && segment >= 0);
+            }
+            __syncwarp();
+
+            // end of segment?
+            if (fragRead == fragWrite)
+                break;
+
+            // clear triangle boundaries
+            temp[threadIdx.x + 16] = 0;
+            __syncwarp();
+
+            // tag triangle boundaries
+            if (triRead + threadIdx.x < triWrite)
+            {
+                int idx = triangleFrag[(triRead + threadIdx.x) & 63] - fragRead;
+                if (idx <= 32)
+                    temp[idx + 16 - 1] = 1;
+            }
+            __syncwarp();
+
+            int ropLaneIdx = threadIdx.x;
+            U32 boundaryMask = __ballot_sync(~0u, temp[ropLaneIdx + 16]);
+
+            // distribute fragments
+            bool hasFragment = (ropLaneIdx < fragWrite - fragRead);
+            U32 fragmentMask = __ballot_sync(~0u, hasFragment);
+            if (hasFragment)
+            {
+                int triBufIdx = (triRead + __popc(boundaryMask & getLaneMaskLt())) & 63;
+                int fragIdx = add_sub(fragRead, ropLaneIdx, triangleFrag[(triBufIdx - 1) & 63]);
+                U64 coverage = triangleCov[triBufIdx];
+                int pixelInTile = findBit(coverage, fragIdx);
+                int dataIdx = triDataIdx[triBufIdx];
+
+                // determine pixel position
+                U32 pixelX = (tileX << CR_TILE_LOG2) + (pixelInTile & 7);
+                U32 pixelY = (tileY << CR_TILE_LOG2) + (pixelInTile >> 3);
+
+                // depth test
+                U32 depth = 0;
+                uint4 td = *((uint4*)triData + dataIdx * (sizeof(CRTriangleData) >> 4));
+
+                depth = td.x * pixelX + td.y * pixelY + td.z;
+                bool zkill = (p.renderModeFlags & CudaRaster::RenderModeFlag_EnableDepthPeeling) && (depth <= tilePeel[pixelInTile]);
+                if (!zkill)
+                {
+                    U32 oldDepth = tileDepth[pixelInTile];
+                    if (depth > oldDepth)
+                        zkill = true;
+                    else if (oldDepth == tileZMax)
+                        tileZUpd = true; // we are replacing previous zmax => need to update
+                }
+
+                U32 ropMask = __ballot_sync(fragmentMask, !zkill);
+                if (!zkill)
+					executeROP(td.w, depth, &tileColor[pixelInTile], &tileDepth[pixelInTile], ropMask);
+            }
+            // no need to sync, as next up is updateTileZMax that does internal warp sync
+
+            // update counters
+            fragRead = ::min(fragRead + 32, fragWrite);
+            triRead += __popc(boundaryMask);
+        }
+
+        // Write tile back to the framebuffer.
+        if (true)
+        {
+            int px = (tileX << CR_TILE_LOG2) + (threadIdx.x & (CR_TILE_SIZE - 1));
+            int py = (tileY << CR_TILE_LOG2) + (threadIdx.x >> CR_TILE_LOG2);
+            U32* pColor = (U32*)p.colorBuffer + p.strideX * p.strideY * blockIdx.z;
+            U32* pDepth = (U32*)p.depthBuffer + p.strideX * p.strideY * blockIdx.z;
+            pColor[px + p.strideX * py] = tileColor[threadIdx.x];
+            pDepth[px + p.strideX * py] = tileDepth[threadIdx.x];
+            pColor[px + p.strideX * (py + 4)] = tileColor[threadIdx.x + 32];
+            pDepth[px + p.strideX * (py + 4)] = tileDepth[threadIdx.x + 32];
+        }
+    }
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/PrivateDefs.hpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/PrivateDefs.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..26133c97d0479c19a61d757c9eac19618dbc8729
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/PrivateDefs.hpp
@@ -0,0 +1,153 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include "Defs.hpp"
+#include "Constants.hpp"
+
+namespace CR
+{
+//------------------------------------------------------------------------
+// Projected triangle.
+//------------------------------------------------------------------------
+
+struct CRTriangleHeader
+{
+    S16 v0x;    // Subpixels relative to viewport center. Valid if triSubtris = 1.
+    S16 v0y;
+    S16 v1x;
+    S16 v1y;
+    S16 v2x;
+    S16 v2y;
+
+    U32 misc;   // triSubtris=1: (zmin:20, f01:4, f12:4, f20:4), triSubtris>=2: (subtriBase)
+};
+
+//------------------------------------------------------------------------
+
+struct CRTriangleData
+{
+    U32 zx;     // zx * sampleX + zy * sampleY + zb = lerp(CR_DEPTH_MIN, CR_DEPTH_MAX, (clipZ / clipW + 1) / 2)
+    U32 zy;
+    U32 zb;
+    U32 id;     // Triangle id.
+};
+
+//------------------------------------------------------------------------
+// Device-side structures.
+//------------------------------------------------------------------------
+
+struct CRAtomics
+{
+    // Setup.
+    S32         numSubtris;         // = numTris
+
+    // Bin.
+    S32         binCounter;         // = 0
+    S32         numBinSegs;         // = 0
+
+    // Coarse.
+    S32         coarseCounter;      // = 0
+    S32         numTileSegs;        // = 0
+    S32         numActiveTiles;     // = 0
+
+    // Fine.
+    S32         fineCounter;        // = 0
+};
+
+//------------------------------------------------------------------------
+
+struct CRImageParams
+{
+    S32         triOffset;          // First triangle index to draw.
+    S32         triCount;           // Number of triangles to draw.
+    S32         binBatchSize;       // Number of triangles per batch.
+};
+
+//------------------------------------------------------------------------
+
+struct CRParams
+{
+    // Common.
+
+    CRAtomics*  atomics;            // Work counters. Per-image.
+    S32         numImages;          // Batch size.
+    S32         totalCount;         // In range mode, total number of triangles to render.
+    S32         instanceMode;       // 0 = range mode, 1 = instance mode.
+
+    S32         numVertices;        // Number of vertices in input buffer, not counting multiples in instance mode.
+    S32         numTriangles;       // Number of triangles in input buffer.
+    void*       vertexBuffer;       // numVertices * float4(x, y, z, w)
+    void*       indexBuffer;        // numTriangles * int3(vi0, vi1, vi2)
+
+    S32         widthPixels;        // Render buffer size in pixels. Must be multiple of tile size (8x8).
+    S32         heightPixels;
+    S32         widthPixelsVp;      // Viewport size in pixels.
+    S32         heightPixelsVp;
+    S32         widthBins;          // widthPixels / CR_BIN_SIZE
+    S32         heightBins;         // heightPixels / CR_BIN_SIZE
+    S32         numBins;            // widthBins * heightBins
+
+    F32         xs;                 // Vertex position adjustments for tiled rendering.
+    F32         ys;
+    F32         xo;
+    F32         yo;
+
+    S32         widthTiles;         // widthPixels / CR_TILE_SIZE
+    S32         heightTiles;        // heightPixels / CR_TILE_SIZE
+    S32         numTiles;           // widthTiles * heightTiles
+
+    U32         renderModeFlags;
+    S32         deferredClear;      // 1 = Clear framebuffer before rendering triangles.
+    U32         clearColor;
+    U32         clearDepth;
+
+    // These are uniform across batch.
+
+    S32         maxSubtris;
+    S32         maxBinSegs;
+    S32         maxTileSegs;
+
+    // Setup output / bin input.
+
+    void*       triSubtris;         // maxSubtris * U8
+    void*       triHeader;          // maxSubtris * CRTriangleHeader
+    void*       triData;            // maxSubtris * CRTriangleData
+
+    // Bin output / coarse input.
+
+    void*       binSegData;         // maxBinSegs * CR_BIN_SEG_SIZE * S32
+    void*       binSegNext;         // maxBinSegs * S32
+    void*       binSegCount;        // maxBinSegs * S32
+    void*       binFirstSeg;        // CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * (S32 segIdx), -1 = none
+    void*       binTotal;           // CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * (S32 numTris)
+
+    // Coarse output / fine input.
+
+    void*       tileSegData;        // maxTileSegs * CR_TILE_SEG_SIZE * S32
+    void*       tileSegNext;        // maxTileSegs * S32
+    void*       tileSegCount;       // maxTileSegs * S32
+    void*       activeTiles;        // CR_MAXTILES_SQR * (S32 tileIdx)
+    void*       tileFirstSeg;       // CR_MAXTILES_SQR * (S32 segIdx), -1 = none
+
+    // Surface buffers. Outer tile offset is baked into pointers.
+
+    void*       colorBuffer;        // sizePixels.x * sizePixels.y * numImages * U32
+    void*       depthBuffer;        // sizePixels.x * sizePixels.y * numImages * U32
+    void*       peelBuffer;         // sizePixels.x * sizePixels.y * numImages * U32, only if peeling enabled.
+    S32         strideX;            // horizontal size in pixels
+    S32         strideY;            // vertical stride in pixels
+
+    // Per-image parameters for first images are embedded here to avoid extra memcpy for small batches.
+
+    CRImageParams imageParamsFirst[CR_EMBED_IMAGE_PARAMS];
+    const CRImageParams* imageParamsExtra; // After CR_EMBED_IMAGE_PARAMS.
+};
+
+//------------------------------------------------------------------------
+}
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl.cpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..f7f05d57f56ed033b34f0bbcef412297b01f5abc
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl.cpp
@@ -0,0 +1,370 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "../../framework.h"
+#include "PrivateDefs.hpp"
+#include "Constants.hpp"
+#include "RasterImpl.hpp"
+#include <cuda_runtime.h>
+
+using namespace CR;
+using std::min;
+using std::max;
+
+//------------------------------------------------------------------------
+// Kernel prototypes and variables.
+
+void triangleSetupKernel (const CRParams p);
+void binRasterKernel     (const CRParams p);
+void coarseRasterKernel  (const CRParams p);
+void fineRasterKernel    (const CRParams p);
+
+//------------------------------------------------------------------------
+
+RasterImpl::RasterImpl(void)
+:   m_renderModeFlags       (0),
+    m_deferredClear         (false),
+    m_clearColor            (0),
+    m_vertexPtr             (NULL),
+    m_indexPtr              (NULL),
+    m_numVertices           (0),
+    m_numTriangles          (0),
+    m_bufferSizesReported   (0),
+
+    m_numImages             (0),
+    m_bufferSizePixels      (0, 0),
+    m_bufferSizeVp          (0, 0),
+    m_sizePixels            (0, 0),
+    m_sizeVp                (0, 0),
+    m_offsetPixels          (0, 0),
+    m_sizeBins              (0, 0),
+    m_numBins               (0),
+    m_sizeTiles             (0, 0),
+    m_numTiles              (0),
+
+    m_numSMs                (1),
+    m_numCoarseBlocksPerSM  (1),
+    m_numFineBlocksPerSM    (1),
+    m_numFineWarpsPerBlock  (1),
+
+    m_maxSubtris            (1),
+    m_maxBinSegs            (1),
+    m_maxTileSegs           (1)
+{
+    // Query relevant device attributes.
+
+    int currentDevice = 0;
+    NVDR_CHECK_CUDA_ERROR(cudaGetDevice(&currentDevice));
+    NVDR_CHECK_CUDA_ERROR(cudaDeviceGetAttribute(&m_numSMs, cudaDevAttrMultiProcessorCount, currentDevice));
+    cudaFuncAttributes attr;
+    NVDR_CHECK_CUDA_ERROR(cudaFuncGetAttributes(&attr, (void*)fineRasterKernel));
+    m_numFineWarpsPerBlock = min(attr.maxThreadsPerBlock / 32, CR_FINE_MAX_WARPS);
+    NVDR_CHECK_CUDA_ERROR(cudaOccupancyMaxActiveBlocksPerMultiprocessor(&m_numCoarseBlocksPerSM, (void*)coarseRasterKernel, 32 * CR_COARSE_WARPS, 0));
+    NVDR_CHECK_CUDA_ERROR(cudaOccupancyMaxActiveBlocksPerMultiprocessor(&m_numFineBlocksPerSM, (void*)fineRasterKernel, 32 * m_numFineWarpsPerBlock, 0));
+
+    // Setup functions.
+
+    NVDR_CHECK_CUDA_ERROR(cudaFuncSetCacheConfig((void*)triangleSetupKernel, cudaFuncCachePreferShared));
+    NVDR_CHECK_CUDA_ERROR(cudaFuncSetCacheConfig((void*)binRasterKernel,     cudaFuncCachePreferShared));
+    NVDR_CHECK_CUDA_ERROR(cudaFuncSetCacheConfig((void*)coarseRasterKernel,  cudaFuncCachePreferShared));
+    NVDR_CHECK_CUDA_ERROR(cudaFuncSetCacheConfig((void*)fineRasterKernel,    cudaFuncCachePreferShared));
+}
+
+//------------------------------------------------------------------------
+
+RasterImpl::~RasterImpl(void)
+{
+    // Empty.
+}
+
+//------------------------------------------------------------------------
+
+void RasterImpl::setBufferSize(Vec3i size)
+{
+    // Internal buffer width and height must be divisible by tile size.
+    int w = (size.x + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+    int h = (size.y + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+
+    m_bufferSizePixels = Vec2i(w, h);
+    m_bufferSizeVp     = Vec2i(size.x, size.y);
+    m_numImages        = size.z;
+
+    m_colorBuffer.reset(w * h * size.z * sizeof(U32));
+    m_depthBuffer.reset(w * h * size.z * sizeof(U32));
+}
+
+//------------------------------------------------------------------------
+
+void RasterImpl::setViewport(Vec2i size, Vec2i offset)
+{
+    // Offset must be divisible by tile size.
+    NVDR_CHECK((offset.x & (CR_TILE_SIZE - 1)) == 0 && (offset.y & (CR_TILE_SIZE - 1)) == 0, "invalid viewport offset");
+
+    // Round internal viewport size to multiples of tile size.
+    int w = (size.x + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+    int h = (size.y + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+
+    m_sizePixels    = Vec2i(w, h);
+    m_offsetPixels  = offset;
+    m_sizeVp        = Vec2i(size.x, size.y);
+    m_sizeTiles.x   = m_sizePixels.x >> CR_TILE_LOG2;
+    m_sizeTiles.y   = m_sizePixels.y >> CR_TILE_LOG2;
+    m_numTiles      = m_sizeTiles.x * m_sizeTiles.y;
+    m_sizeBins.x    = (m_sizeTiles.x + CR_BIN_SIZE - 1) >> CR_BIN_LOG2;
+    m_sizeBins.y    = (m_sizeTiles.y + CR_BIN_SIZE - 1) >> CR_BIN_LOG2;
+    m_numBins       = m_sizeBins.x * m_sizeBins.y;
+}
+
+void RasterImpl::swapDepthAndPeel(void)
+{
+    m_peelBuffer.reset(m_depthBuffer.getSize()); // Ensure equal size and valid pointer.
+
+    void* tmp = m_depthBuffer.getPtr();
+    m_depthBuffer.setPtr(m_peelBuffer.getPtr());
+    m_peelBuffer.setPtr(tmp);
+}
+
+//------------------------------------------------------------------------
+
+bool RasterImpl::drawTriangles(const Vec2i* ranges, bool peel, cudaStream_t stream)
+{
+    bool instanceMode = (!ranges);
+
+    int maxSubtrisSlack     = 4096;     // x 81B    = 324KB
+    int maxBinSegsSlack     = 256;      // x 2137B  = 534KB
+    int maxTileSegsSlack    = 4096;     // x 136B   = 544KB
+
+    // Resize atomics as needed.
+    m_crAtomics    .grow(m_numImages * sizeof(CRAtomics));
+    m_crAtomicsHost.grow(m_numImages * sizeof(CRAtomics));
+
+    // Size of these buffers doesn't depend on input.
+    m_binFirstSeg  .grow(m_numImages * CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * sizeof(S32));
+    m_binTotal     .grow(m_numImages * CR_MAXBINS_SQR * CR_BIN_STREAMS_SIZE * sizeof(S32));
+    m_activeTiles  .grow(m_numImages * CR_MAXTILES_SQR * sizeof(S32));
+    m_tileFirstSeg .grow(m_numImages * CR_MAXTILES_SQR * sizeof(S32));
+
+    // Construct per-image parameters and determine worst-case buffer sizes.
+    m_crImageParamsHost.grow(m_numImages * sizeof(CRImageParams));
+    CRImageParams* imageParams = (CRImageParams*)m_crImageParamsHost.getPtr();
+    for (int i=0; i < m_numImages; i++)
+    {
+        CRImageParams& ip = imageParams[i];
+
+        int roundSize  = CR_BIN_WARPS * 32;
+        int minBatches = CR_BIN_STREAMS_SIZE * 2;
+        int maxRounds  = 32;
+
+        ip.triOffset = instanceMode ? 0 : ranges[i].x;
+        ip.triCount  = instanceMode ? m_numTriangles : ranges[i].y;
+        ip.binBatchSize = min(max(ip.triCount / (roundSize * minBatches), 1), maxRounds) * roundSize;
+
+        m_maxSubtris  = max(m_maxSubtris,  min(ip.triCount + maxSubtrisSlack, CR_MAXSUBTRIS_SIZE));
+        m_maxBinSegs  = max(m_maxBinSegs,  max(m_numBins * CR_BIN_STREAMS_SIZE, (ip.triCount - 1) / CR_BIN_SEG_SIZE + 1) + maxBinSegsSlack);
+        m_maxTileSegs = max(m_maxTileSegs, max(m_numTiles, (ip.triCount - 1) / CR_TILE_SEG_SIZE + 1) + maxTileSegsSlack);
+    }
+
+    // Retry until successful.
+
+    for (;;)
+    {
+        // Allocate buffers.
+        m_triSubtris.reset(m_numImages * m_maxSubtris * sizeof(U8));
+        m_triHeader .reset(m_numImages * m_maxSubtris * sizeof(CRTriangleHeader));
+        m_triData   .reset(m_numImages * m_maxSubtris * sizeof(CRTriangleData));
+
+        m_binSegData .reset(m_numImages * m_maxBinSegs * CR_BIN_SEG_SIZE * sizeof(S32));
+        m_binSegNext .reset(m_numImages * m_maxBinSegs * sizeof(S32));
+        m_binSegCount.reset(m_numImages * m_maxBinSegs * sizeof(S32));
+
+        m_tileSegData .reset(m_numImages * m_maxTileSegs * CR_TILE_SEG_SIZE * sizeof(S32));
+        m_tileSegNext .reset(m_numImages * m_maxTileSegs * sizeof(S32));
+        m_tileSegCount.reset(m_numImages * m_maxTileSegs * sizeof(S32));
+
+        // Report if buffers grow from last time.
+        size_t sizesTotal = getTotalBufferSizes();
+        if (sizesTotal > m_bufferSizesReported)
+        {
+            size_t sizesMB = ((sizesTotal - 1) >> 20) + 1; // Round up.
+            sizesMB = ((sizesMB + 9) / 10) * 10; // 10MB granularity enough in this day and age.
+            LOG(INFO) << "Internal buffers grown to " << sizesMB << " MB";
+            m_bufferSizesReported = sizesMB << 20;
+        }
+
+        // Launch stages. Blocks until everything is done.
+        launchStages(instanceMode, peel, stream);
+
+        // Peeling iteration cannot fail, so no point checking things further.
+        if (peel)
+            break;
+
+        // Atomics after coarse stage are now available.
+        CRAtomics* atomics = (CRAtomics*)m_crAtomicsHost.getPtr();
+
+        // Success?
+        bool failed = false;
+        for (int i=0; i < m_numImages; i++)
+        {
+            const CRAtomics& a = atomics[i];
+            failed = failed || (a.numSubtris > m_maxSubtris) || (a.numBinSegs > m_maxBinSegs) || (a.numTileSegs > m_maxTileSegs);
+        }
+        if (!failed)
+            break; // Success!
+
+        // If we were already at maximum capacity, no can do.
+        if (m_maxSubtris == CR_MAXSUBTRIS_SIZE)
+            return false;
+
+        // Enlarge buffers and try again.
+        for (int i=0; i < m_numImages; i++)
+        {
+            const CRAtomics& a = atomics[i];
+            m_maxSubtris  = max(m_maxSubtris,  min(a.numSubtris + maxSubtrisSlack, CR_MAXSUBTRIS_SIZE));
+            m_maxBinSegs  = max(m_maxBinSegs,  a.numBinSegs + maxBinSegsSlack);
+            m_maxTileSegs = max(m_maxTileSegs, a.numTileSegs + maxTileSegsSlack);
+        }
+    }
+
+    m_deferredClear = false;
+    return true; // Success.
+}
+
+//------------------------------------------------------------------------
+
+size_t RasterImpl::getTotalBufferSizes(void) const
+{
+    return
+        m_colorBuffer.getSize() + m_depthBuffer.getSize() + // Don't include atomics and image params.
+        m_triSubtris.getSize() + m_triHeader.getSize() + m_triData.getSize() +
+        m_binFirstSeg.getSize() + m_binTotal.getSize() + m_binSegData.getSize() + m_binSegNext.getSize() + m_binSegCount.getSize() +
+        m_activeTiles.getSize() + m_tileFirstSeg.getSize() + m_tileSegData.getSize() + m_tileSegNext.getSize() + m_tileSegCount.getSize();
+}
+
+//------------------------------------------------------------------------
+
+void RasterImpl::launchStages(bool instanceMode, bool peel, cudaStream_t stream)
+{
+    CRImageParams* imageParams = (CRImageParams*)m_crImageParamsHost.getPtr();
+
+    // Unless peeling, initialize atomics to mostly zero.
+    CRAtomics* atomics = (CRAtomics*)m_crAtomicsHost.getPtr();
+    if (!peel)
+    {
+        memset(atomics, 0, m_numImages * sizeof(CRAtomics));
+        for (int i=0; i < m_numImages; i++)
+            atomics[i].numSubtris = imageParams[i].triCount;
+    }
+
+    // Copy to device. If peeling, this is the state after coarse raster launch on first iteration.
+    NVDR_CHECK_CUDA_ERROR(cudaMemcpyAsync(m_crAtomics.getPtr(), atomics, m_numImages * sizeof(CRAtomics), cudaMemcpyHostToDevice, stream));
+
+    // Copy per-image parameters if there are more than fits in launch parameter block and we haven't done it already.
+    if (!peel && m_numImages > CR_EMBED_IMAGE_PARAMS)
+    {
+        int numImageParamsExtra = m_numImages - CR_EMBED_IMAGE_PARAMS;
+        m_crImageParamsExtra.grow(numImageParamsExtra * sizeof(CRImageParams));
+        NVDR_CHECK_CUDA_ERROR(cudaMemcpyAsync(m_crImageParamsExtra.getPtr(), imageParams + CR_EMBED_IMAGE_PARAMS, numImageParamsExtra * sizeof(CRImageParams), cudaMemcpyHostToDevice, stream));
+    }
+
+    // Set global parameters.
+    CRParams p;
+    {
+        p.atomics           = (CRAtomics*)m_crAtomics.getPtr();
+        p.numImages         = m_numImages;
+        p.totalCount        = 0; // Only relevant in range mode.
+        p.instanceMode      = instanceMode ? 1 : 0;
+
+        p.numVertices       = m_numVertices;
+        p.numTriangles      = m_numTriangles;
+        p.vertexBuffer      = m_vertexPtr;
+        p.indexBuffer       = m_indexPtr;
+
+        p.widthPixels       = m_sizePixels.x;
+        p.heightPixels      = m_sizePixels.y;
+        p.widthPixelsVp     = m_sizeVp.x;
+        p.heightPixelsVp    = m_sizeVp.y;
+        p.widthBins         = m_sizeBins.x;
+        p.heightBins        = m_sizeBins.y;
+        p.numBins           = m_numBins;
+
+        p.xs                = (float)m_bufferSizeVp.x / (float)m_sizeVp.x;
+        p.ys                = (float)m_bufferSizeVp.y / (float)m_sizeVp.y;
+        p.xo                = (float)(m_bufferSizeVp.x - m_sizeVp.x - 2 * m_offsetPixels.x) / (float)m_sizeVp.x;
+        p.yo                = (float)(m_bufferSizeVp.y - m_sizeVp.y - 2 * m_offsetPixels.y) / (float)m_sizeVp.y;
+
+        p.widthTiles        = m_sizeTiles.x;
+        p.heightTiles       = m_sizeTiles.y;
+        p.numTiles          = m_numTiles;
+
+        p.renderModeFlags   = m_renderModeFlags;
+        p.deferredClear     = m_deferredClear ? 1 : 0;
+        p.clearColor        = m_clearColor;
+        p.clearDepth        = CR_DEPTH_MAX;
+
+        p.maxSubtris        = m_maxSubtris;
+        p.maxBinSegs        = m_maxBinSegs;
+        p.maxTileSegs       = m_maxTileSegs;
+
+        p.triSubtris        = m_triSubtris.getPtr();
+        p.triHeader         = m_triHeader.getPtr();
+        p.triData           = m_triData.getPtr();
+        p.binSegData        = m_binSegData.getPtr();
+        p.binSegNext        = m_binSegNext.getPtr();
+        p.binSegCount       = m_binSegCount.getPtr();
+        p.binFirstSeg       = m_binFirstSeg.getPtr();
+        p.binTotal          = m_binTotal.getPtr();
+        p.tileSegData       = m_tileSegData.getPtr();
+        p.tileSegNext       = m_tileSegNext.getPtr();
+        p.tileSegCount      = m_tileSegCount.getPtr();
+        p.activeTiles       = m_activeTiles.getPtr();
+        p.tileFirstSeg      = m_tileFirstSeg.getPtr();
+
+        size_t byteOffset = ((size_t)m_offsetPixels.x + (size_t)m_offsetPixels.y * (size_t)p.strideX) * sizeof(U32);
+        p.colorBuffer       = m_colorBuffer.getPtr(byteOffset);
+        p.depthBuffer       = m_depthBuffer.getPtr(byteOffset);
+        p.peelBuffer        = (m_renderModeFlags & CudaRaster::RenderModeFlag_EnableDepthPeeling) ? m_peelBuffer.getPtr(byteOffset) : 0;
+        p.strideX           = m_bufferSizePixels.x;
+        p.strideY           = m_bufferSizePixels.y;
+
+        memcpy(&p.imageParamsFirst, imageParams, min(m_numImages, CR_EMBED_IMAGE_PARAMS) * sizeof(CRImageParams));
+        p.imageParamsExtra  = (CRImageParams*)m_crImageParamsExtra.getPtr();
+    }
+
+    // Setup block sizes.
+
+    dim3 brBlock(32, CR_BIN_WARPS);
+    dim3 crBlock(32, CR_COARSE_WARPS);
+    dim3 frBlock(32, m_numFineWarpsPerBlock);
+    void* args[] = {&p};
+
+    // Launch stages from setup to coarse and copy atomics to host only if this is not a single-tile peeling iteration.
+    if (!peel)
+    {
+        if (instanceMode)
+        {
+            int setupBlocks = (m_numTriangles - 1) / (32 * CR_SETUP_WARPS) + 1;
+            NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)triangleSetupKernel, dim3(setupBlocks, 1, m_numImages), dim3(32, CR_SETUP_WARPS), args, 0, stream));
+        }
+        else
+        {
+            for (int i=0; i < m_numImages; i++)
+                p.totalCount += imageParams[i].triCount;
+            int setupBlocks = (p.totalCount - 1) / (32 * CR_SETUP_WARPS) + 1;
+            NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)triangleSetupKernel, dim3(setupBlocks, 1, 1), dim3(32, CR_SETUP_WARPS), args, 0, stream));
+        }
+        NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)binRasterKernel, dim3(CR_BIN_STREAMS_SIZE, 1, m_numImages), brBlock, args, 0, stream));
+        NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)coarseRasterKernel, dim3(m_numSMs * m_numCoarseBlocksPerSM, 1, m_numImages), crBlock, args, 0, stream));
+        NVDR_CHECK_CUDA_ERROR(cudaMemcpyAsync(m_crAtomicsHost.getPtr(), m_crAtomics.getPtr(), sizeof(CRAtomics) * m_numImages, cudaMemcpyDeviceToHost, stream));
+    }
+
+    // Fine rasterizer is launched always.
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)fineRasterKernel, dim3(m_numSMs * m_numFineBlocksPerSM, 1, m_numImages), frBlock, args, 0, stream));
+    NVDR_CHECK_CUDA_ERROR(cudaStreamSynchronize(stream));
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl.hpp b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..d594acdfeb2a83133726a6dfd594b3ccad0d74cc
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl.hpp
@@ -0,0 +1,102 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include "PrivateDefs.hpp"
+#include "Buffer.hpp"
+#include "../CudaRaster.hpp"
+
+namespace CR
+{
+//------------------------------------------------------------------------
+
+class RasterImpl
+{
+public:
+					        RasterImpl				(void);
+					        ~RasterImpl				(void);
+
+    void                    setBufferSize           (Vec3i size);
+    void                    setViewport             (Vec2i size, Vec2i offset);
+    void                    setRenderModeFlags      (U32 flags) { m_renderModeFlags = flags; }
+    void                    deferredClear           (U32 color) { m_deferredClear = true; m_clearColor = color; }
+    void                    setVertexBuffer         (void* ptr, int numVertices) { m_vertexPtr = ptr; m_numVertices = numVertices; } // GPU pointer.
+    void                    setIndexBuffer          (void* ptr, int numTriangles) { m_indexPtr = ptr; m_numTriangles = numTriangles; } // GPU pointer.
+    bool                    drawTriangles           (const Vec2i* ranges, bool peel, cudaStream_t stream);
+    void*                   getColorBuffer          (void) { return m_colorBuffer.getPtr(); } // GPU pointer.
+    void*                   getDepthBuffer          (void) { return m_depthBuffer.getPtr(); } // GPU pointer.
+    void                    swapDepthAndPeel        (void);
+    size_t                  getTotalBufferSizes     (void) const;
+
+private:
+    void                    launchStages            (bool instanceMode, bool peel, cudaStream_t stream);
+
+    // State.
+
+    unsigned int            m_renderModeFlags;
+    bool                    m_deferredClear;
+    unsigned int            m_clearColor;
+    void*                   m_vertexPtr;
+    void*                   m_indexPtr;
+    int                     m_numVertices;          // Input buffer size.
+    int                     m_numTriangles;         // Input buffer size.
+    size_t                  m_bufferSizesReported;  // Previously reported buffer sizes.
+
+    // Surfaces.
+
+    Buffer                  m_colorBuffer;
+    Buffer                  m_depthBuffer;
+    Buffer                  m_peelBuffer;
+    int                     m_numImages;
+    Vec2i                   m_bufferSizePixels;     // Internal buffer size.
+    Vec2i                   m_bufferSizeVp;         // Total viewport size.
+    Vec2i                   m_sizePixels;           // Internal size at which all computation is done, buffers reserved, etc.
+    Vec2i                   m_sizeVp;               // Size to which output will be cropped outside, determines viewport size.
+    Vec2i                   m_offsetPixels;         // Viewport offset for tiled rendering.
+    Vec2i                   m_sizeBins;
+    S32                     m_numBins;
+    Vec2i                   m_sizeTiles;
+    S32                     m_numTiles;
+
+    // Launch sizes etc.
+
+    S32                     m_numSMs;
+    S32                     m_numCoarseBlocksPerSM;
+    S32                     m_numFineBlocksPerSM;
+    S32                     m_numFineWarpsPerBlock;
+
+    // Global intermediate buffers. Individual images have offsets to these.
+
+    Buffer                  m_crAtomics;
+    HostBuffer              m_crAtomicsHost;
+    HostBuffer              m_crImageParamsHost;
+    Buffer                  m_crImageParamsExtra;
+    Buffer                  m_triSubtris;
+    Buffer                  m_triHeader;
+    Buffer                  m_triData;
+    Buffer                  m_binFirstSeg;
+    Buffer                  m_binTotal;
+    Buffer                  m_binSegData;
+    Buffer                  m_binSegNext;
+	Buffer                  m_binSegCount;
+    Buffer                  m_activeTiles;
+    Buffer                  m_tileFirstSeg;
+    Buffer                  m_tileSegData;
+    Buffer                  m_tileSegNext;
+    Buffer                  m_tileSegCount;
+
+    // Actual buffer sizes.
+
+    S32                     m_maxSubtris;
+    S32                     m_maxBinSegs;
+    S32                     m_maxTileSegs;
+};
+
+//------------------------------------------------------------------------
+} // namespace CR
+
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl_.cu b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl_.cu
new file mode 100644
index 0000000000000000000000000000000000000000..43b1edf04a36d52d22aac8465b584e576ecb723b
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/RasterImpl_.cu
@@ -0,0 +1,37 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "../CudaRaster.hpp"
+#include "PrivateDefs.hpp"
+#include "Constants.hpp"
+#include "Util.inl"
+
+namespace CR
+{
+
+//------------------------------------------------------------------------
+// Stage implementations.
+//------------------------------------------------------------------------
+
+#include "TriangleSetup.inl"
+#include "BinRaster.inl"
+#include "CoarseRaster.inl"
+#include "FineRaster.inl"
+
+}
+
+//------------------------------------------------------------------------
+// Stage entry points.
+//------------------------------------------------------------------------
+
+__global__ void __launch_bounds__(CR_SETUP_WARPS * 32, CR_SETUP_OPT_BLOCKS)  triangleSetupKernel (const CR::CRParams p)  { CR::triangleSetupImpl(p); }
+__global__ void __launch_bounds__(CR_BIN_WARPS * 32, 1)                      binRasterKernel     (const CR::CRParams p)  { CR::binRasterImpl(p); }
+__global__ void __launch_bounds__(CR_COARSE_WARPS * 32, 1)                   coarseRasterKernel  (const CR::CRParams p)  { CR::coarseRasterImpl(p); }
+__global__ void __launch_bounds__(CR_FINE_MAX_WARPS * 32, 1)                 fineRasterKernel    (const CR::CRParams p)  { CR::fineRasterImpl(p); }
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/TriangleSetup.inl b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/TriangleSetup.inl
new file mode 100644
index 0000000000000000000000000000000000000000..276f0a40ee7ddd3010fed13aebc2cf4fd37011a9
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/TriangleSetup.inl
@@ -0,0 +1,402 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void snapTriangle(
+    const CRParams& p,
+    float4 v0, float4 v1, float4 v2,
+    int2& p0, int2& p1, int2& p2, float3& rcpW, int2& lo, int2& hi)
+{
+    F32 viewScaleX = (F32)(p.widthPixelsVp  << (CR_SUBPIXEL_LOG2 - 1));
+    F32 viewScaleY = (F32)(p.heightPixelsVp << (CR_SUBPIXEL_LOG2 - 1));
+    rcpW = make_float3(1.0f / v0.w, 1.0f / v1.w, 1.0f / v2.w);
+    p0 = make_int2(f32_to_s32_sat(v0.x * rcpW.x * viewScaleX), f32_to_s32_sat(v0.y * rcpW.x * viewScaleY));
+    p1 = make_int2(f32_to_s32_sat(v1.x * rcpW.y * viewScaleX), f32_to_s32_sat(v1.y * rcpW.y * viewScaleY));
+    p2 = make_int2(f32_to_s32_sat(v2.x * rcpW.z * viewScaleX), f32_to_s32_sat(v2.y * rcpW.z * viewScaleY));
+    lo = make_int2(min_min(p0.x, p1.x, p2.x), min_min(p0.y, p1.y, p2.y));
+    hi = make_int2(max_max(p0.x, p1.x, p2.x), max_max(p0.y, p1.y, p2.y));
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U32 cover8x8_selectFlips(S32 dx, S32 dy) // 10 instr
+{
+    U32 flips = 0;
+    if (dy > 0 || (dy == 0 && dx <= 0))
+        flips ^= (1 << CR_FLIPBIT_FLIP_X) ^ (1 << CR_FLIPBIT_FLIP_Y) ^ (1 << CR_FLIPBIT_COMPL);
+    if (dx > 0)
+        flips ^= (1 << CR_FLIPBIT_FLIP_X) ^ (1 << CR_FLIPBIT_FLIP_Y);
+    if (::abs(dx) < ::abs(dy))
+        flips ^= (1 << CR_FLIPBIT_SWAP_XY) ^ (1 << CR_FLIPBIT_FLIP_Y);
+    return flips;
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ bool prepareTriangle(
+    const CRParams& p,
+    int2 p0, int2 p1, int2 p2, int2 lo, int2 hi,
+    int2& d1, int2& d2, S32& area)
+{
+    // Backfacing or degenerate => cull.
+
+    d1 = make_int2(p1.x - p0.x, p1.y - p0.y);
+    d2 = make_int2(p2.x - p0.x, p2.y - p0.y);
+    area = d1.x * d2.y - d1.y * d2.x;
+
+    if (area == 0)
+        return false; // Degenerate.
+
+    if (area < 0 && (p.renderModeFlags & CudaRaster::RenderModeFlag_EnableBackfaceCulling) != 0)
+        return false; // Backfacing.
+
+    // AABB falls between samples => cull.
+
+    int sampleSize = 1 << CR_SUBPIXEL_LOG2;
+    int biasX = (p.widthPixelsVp  << (CR_SUBPIXEL_LOG2 - 1)) - (sampleSize >> 1);
+    int biasY = (p.heightPixelsVp << (CR_SUBPIXEL_LOG2 - 1)) - (sampleSize >> 1);
+    int lox = (int)add_add(lo.x, sampleSize - 1, biasX) & -sampleSize;
+    int loy = (int)add_add(lo.y, sampleSize - 1, biasY) & -sampleSize;
+    int hix = (hi.x + biasX) & -sampleSize;
+    int hiy = (hi.y + biasY) & -sampleSize;
+
+    if (lox > hix || loy > hiy)
+        return false; // Between pixels.
+
+    // AABB covers 1 or 2 samples => cull if they are not covered.
+
+    int diff = add_sub(hix, hiy, lox) - loy;
+    if (diff <= sampleSize)
+    {
+        int2 t0 = make_int2(add_sub(p0.x, biasX, lox), add_sub(p0.y, biasY, loy));
+        int2 t1 = make_int2(add_sub(p1.x, biasX, lox), add_sub(p1.y, biasY, loy));
+        int2 t2 = make_int2(add_sub(p2.x, biasX, lox), add_sub(p2.y, biasY, loy));
+        S32 e0 = t0.x * t1.y - t0.y * t1.x;
+        S32 e1 = t1.x * t2.y - t1.y * t2.x;
+        S32 e2 = t2.x * t0.y - t2.y * t0.x;
+        if (area < 0)
+        {
+            e0 = -e0;
+            e1 = -e1;
+            e2 = -e2;
+        }
+
+        if (e0 < 0 || e1 < 0 || e2 < 0)
+        {
+            if (diff == 0)
+                return false; // Between pixels.
+
+            t0 = make_int2(add_sub(p0.x, biasX, hix), add_sub(p0.y, biasY, hiy));
+            t1 = make_int2(add_sub(p1.x, biasX, hix), add_sub(p1.y, biasY, hiy));
+            t2 = make_int2(add_sub(p2.x, biasX, hix), add_sub(p2.y, biasY, hiy));
+            e0 = t0.x * t1.y - t0.y * t1.x;
+            e1 = t1.x * t2.y - t1.y * t2.x;
+            e2 = t2.x * t0.y - t2.y * t0.x;
+            if (area < 0)
+            {
+                e0 = -e0;
+                e1 = -e1;
+                e2 = -e2;
+            }
+
+            if (e0 < 0 || e1 < 0 || e2 < 0)
+                return false; // Between pixels.
+        }
+    }
+
+    // Otherwise => proceed to output the triangle.
+
+    return true; // Visible.
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void setupTriangle(
+    const CRParams& p,
+    CRTriangleHeader* th, CRTriangleData* td, int triId,
+    float v0z, float v1z, float v2z,
+    int2 p0, int2 p1, int2 p2, float3 rcpW,
+    int2 d1, int2 d2, S32 area)
+{
+    // Swap vertices 1 and 2 if area is negative. Only executed if backface culling is
+    // disabled (if it is enabled, we never come here with area < 0).
+
+    if (area < 0)
+    {
+        swap(d1, d2);
+        swap(p1, p2);
+        swap(v1z, v2z);
+        swap(rcpW.y, rcpW.z);
+        area = -area;
+    }
+
+    int2 wv0;
+    wv0.x = p0.x + (p.widthPixelsVp  << (CR_SUBPIXEL_LOG2 - 1));
+    wv0.y = p0.y + (p.heightPixelsVp << (CR_SUBPIXEL_LOG2 - 1));
+
+    // Setup depth plane equation.
+
+    F32 zcoef = (F32)(CR_DEPTH_MAX - CR_DEPTH_MIN) * 0.5f;
+    F32 zbias = (F32)(CR_DEPTH_MAX + CR_DEPTH_MIN) * 0.5f;
+    float3 zvert = make_float3(
+        (v0z * zcoef) * rcpW.x + zbias,
+        (v1z * zcoef) * rcpW.y + zbias,
+        (v2z * zcoef) * rcpW.z + zbias
+    );
+    int2 zv0 = make_int2(
+        wv0.x - (1 << (CR_SUBPIXEL_LOG2 - 1)),
+        wv0.y - (1 << (CR_SUBPIXEL_LOG2 - 1))
+    );
+    uint3 zpleq = setupPleq(zvert, zv0, d1, d2, 1.0f / (F32)area);
+
+    U32 zmin = f32_to_u32_sat(fminf(fminf(zvert.x, zvert.y), zvert.z) - (F32)CR_LERP_ERROR(0));
+
+    // Write CRTriangleData.
+
+    *(uint4*)td = make_uint4(zpleq.x, zpleq.y, zpleq.z, triId);
+
+    // Determine flipbits.
+
+    U32 f01 = cover8x8_selectFlips(d1.x, d1.y);
+    U32 f12 = cover8x8_selectFlips(d2.x - d1.x, d2.y - d1.y);
+    U32 f20 = cover8x8_selectFlips(-d2.x, -d2.y);
+
+    // Write CRTriangleHeader.
+
+    *(uint4*)th = make_uint4(
+        prmt(p0.x, p0.y, 0x5410),
+        prmt(p1.x, p1.y, 0x5410),
+        prmt(p2.x, p2.y, 0x5410),
+        (zmin & 0xfffff000u) | (f01 << 6) | (f12 << 2) | (f20 >> 2));
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void triangleSetupImpl(const CRParams p)
+{
+    __shared__ F32 s_bary[CR_SETUP_WARPS * 32][18];
+    F32* bary = s_bary[threadIdx.x + threadIdx.y * 32];
+
+    // Compute task and image indices.
+
+    int taskIdx = threadIdx.x + 32 * (threadIdx.y + CR_SETUP_WARPS * blockIdx.x);
+    int imageIdx = 0;
+    if (p.instanceMode)
+    {
+        imageIdx = blockIdx.z;
+        if (taskIdx >= p.numTriangles)
+            return;
+    }
+    else
+    {
+        while (imageIdx < p.numImages)
+        {
+            int count = getImageParams(p, imageIdx).triCount;
+            if (taskIdx < count)
+                break;
+            taskIdx -= count;
+            imageIdx += 1;
+        }
+        if (imageIdx == p.numImages)
+            return;
+    }
+
+    // Per-image data structures.
+
+    const CRImageParams& ip = getImageParams(p, imageIdx);
+    CRAtomics& atomics = p.atomics[imageIdx];
+
+    const int*          indexBuffer = (const int*)p.indexBuffer;
+    U8*                 triSubtris  = (U8*)p.triSubtris               + imageIdx * p.maxSubtris;
+    CRTriangleHeader*   triHeader   = (CRTriangleHeader*)p.triHeader  + imageIdx * p.maxSubtris;
+    CRTriangleData*     triData     = (CRTriangleData*)p.triData      + imageIdx * p.maxSubtris;
+
+    // Determine triangle index.
+
+    int triIdx = taskIdx;
+    if (!p.instanceMode)
+        triIdx += ip.triOffset;
+
+    // Read vertex indices.
+
+    if ((U32)triIdx >= (U32)p.numTriangles)
+    {
+        // Bad triangle index.
+        triSubtris[taskIdx] = 0;
+        return;
+    }
+
+    uint4 vidx;
+    vidx.x = indexBuffer[triIdx * 3 + 0];
+    vidx.y = indexBuffer[triIdx * 3 + 1];
+    vidx.z = indexBuffer[triIdx * 3 + 2];
+    vidx.w = triIdx + 1; // Triangle index.
+
+    if (vidx.x >= (U32)p.numVertices ||
+        vidx.y >= (U32)p.numVertices ||
+        vidx.z >= (U32)p.numVertices)
+    {
+        // Bad vertex index.
+        triSubtris[taskIdx] = 0;
+        return;
+    }
+
+    // Read vertex positions.
+
+    const float4* vertexBuffer = (const float4*)p.vertexBuffer;
+    if (p.instanceMode)
+        vertexBuffer += p.numVertices * imageIdx; // Instance offset.
+
+    float4 v0 = vertexBuffer[vidx.x];
+    float4 v1 = vertexBuffer[vidx.y];
+    float4 v2 = vertexBuffer[vidx.z];
+
+    // Adjust vertex positions according to current viewport size and offset.
+
+    v0.x = v0.x * p.xs + v0.w * p.xo;
+    v0.y = v0.y * p.ys + v0.w * p.yo;
+    v1.x = v1.x * p.xs + v1.w * p.xo;
+    v1.y = v1.y * p.ys + v1.w * p.yo;
+    v2.x = v2.x * p.xs + v2.w * p.xo;
+    v2.y = v2.y * p.ys + v2.w * p.yo;
+
+    // Outside view frustum => cull.
+
+    if (v0.w < fabsf(v0.x) | v0.w < fabsf(v0.y) | v0.w < fabsf(v0.z))
+    {
+        if ((v0.w < +v0.x & v1.w < +v1.x & v2.w < +v2.x) |
+            (v0.w < -v0.x & v1.w < -v1.x & v2.w < -v2.x) |
+            (v0.w < +v0.y & v1.w < +v1.y & v2.w < +v2.y) |
+            (v0.w < -v0.y & v1.w < -v1.y & v2.w < -v2.y) |
+            (v0.w < +v0.z & v1.w < +v1.z & v2.w < +v2.z) |
+            (v0.w < -v0.z & v1.w < -v1.z & v2.w < -v2.z))
+        {
+            triSubtris[taskIdx] = 0;
+            return;
+        }
+    }
+
+    // Inside depth range => try to snap vertices.
+
+    if (v0.w >= fabsf(v0.z) & v1.w >= fabsf(v1.z) & v2.w >= fabsf(v2.z))
+    {
+        // Inside S16 range and small enough => fast path.
+        // Note: aabbLimit comes from the fact that cover8x8
+        // does not support guardband with maximal viewport.
+
+        int2 p0, p1, p2, lo, hi;
+        float3 rcpW;
+
+        snapTriangle(p, v0, v1, v2, p0, p1, p2, rcpW, lo, hi);
+        S32 loxy = ::min(lo.x, lo.y);
+        S32 hixy = ::max(hi.x, hi.y);
+        S32 aabbLimit = (1 << (CR_MAXVIEWPORT_LOG2 + CR_SUBPIXEL_LOG2)) - 1;
+
+        if (loxy >= -32768 && hixy <= 32767 && hixy - loxy <= aabbLimit)
+        {
+            int2 d1, d2;
+            S32 area;
+            bool res = prepareTriangle(p, p0, p1, p2, lo, hi, d1, d2, area);
+            triSubtris[taskIdx] = res ? 1 : 0;
+
+            if (res)
+                setupTriangle(
+                    p,
+                    &triHeader[taskIdx], &triData[taskIdx], vidx.w,
+                    v0.z, v1.z, v2.z,
+                    p0, p1, p2, rcpW,
+                    d1, d2, area);
+
+            return;
+        }
+    }
+
+    // Clip to view frustum.
+
+    float4 ov0 = v0;
+    float4 od1 = make_float4(v1.x - v0.x, v1.y - v0.y, v1.z - v0.z, v1.w - v0.w);
+    float4 od2 = make_float4(v2.x - v0.x, v2.y - v0.y, v2.z - v0.z, v2.w - v0.w);
+    int numVerts = clipTriangleWithFrustum(bary, &ov0.x, &v1.x, &v2.x, &od1.x, &od2.x);
+
+    // Count non-culled subtriangles.
+
+    v0.x = ov0.x + od1.x * bary[0] + od2.x * bary[1];
+    v0.y = ov0.y + od1.y * bary[0] + od2.y * bary[1];
+    v0.z = ov0.z + od1.z * bary[0] + od2.z * bary[1];
+    v0.w = ov0.w + od1.w * bary[0] + od2.w * bary[1];
+    v1.x = ov0.x + od1.x * bary[2] + od2.x * bary[3];
+    v1.y = ov0.y + od1.y * bary[2] + od2.y * bary[3];
+    v1.z = ov0.z + od1.z * bary[2] + od2.z * bary[3];
+    v1.w = ov0.w + od1.w * bary[2] + od2.w * bary[3];
+    float4 tv1 = v1;
+
+    int numSubtris = 0;
+    for (int i = 2; i < numVerts; i++)
+    {
+        v2.x = ov0.x + od1.x * bary[i * 2 + 0] + od2.x * bary[i * 2 + 1];
+        v2.y = ov0.y + od1.y * bary[i * 2 + 0] + od2.y * bary[i * 2 + 1];
+        v2.z = ov0.z + od1.z * bary[i * 2 + 0] + od2.z * bary[i * 2 + 1];
+        v2.w = ov0.w + od1.w * bary[i * 2 + 0] + od2.w * bary[i * 2 + 1];
+
+        int2 p0, p1, p2, lo, hi, d1, d2;
+        float3 rcpW;
+        S32 area;
+
+        snapTriangle(p, v0, v1, v2, p0, p1, p2, rcpW, lo, hi);
+        if (prepareTriangle(p, p0, p1, p2, lo, hi, d1, d2, area))
+            numSubtris++;
+
+        v1 = v2;
+    }
+
+    triSubtris[taskIdx] = numSubtris;
+
+    // Multiple subtriangles => allocate.
+
+    int subtriBase = taskIdx;
+    if (numSubtris > 1)
+    {
+        subtriBase = atomicAdd(&atomics.numSubtris, numSubtris);
+        triHeader[taskIdx].misc = subtriBase;
+        if (subtriBase + numSubtris > p.maxSubtris)
+            numVerts = 0;
+    }
+
+    // Setup subtriangles.
+
+    v1 = tv1;
+    for (int i = 2; i < numVerts; i++)
+    {
+        v2.x = ov0.x + od1.x * bary[i * 2 + 0] + od2.x * bary[i * 2 + 1];
+        v2.y = ov0.y + od1.y * bary[i * 2 + 0] + od2.y * bary[i * 2 + 1];
+        v2.z = ov0.z + od1.z * bary[i * 2 + 0] + od2.z * bary[i * 2 + 1];
+        v2.w = ov0.w + od1.w * bary[i * 2 + 0] + od2.w * bary[i * 2 + 1];
+
+        int2 p0, p1, p2, lo, hi, d1, d2;
+        float3 rcpW;
+        S32 area;
+
+        snapTriangle(p, v0, v1, v2, p0, p1, p2, rcpW, lo, hi);
+        if (prepareTriangle(p, p0, p1, p2, lo, hi, d1, d2, area))
+        {
+            setupTriangle(
+                p,
+                &triHeader[subtriBase], &triData[subtriBase], vidx.w,
+                v0.z, v1.z, v2.z,
+                p0, p1, p2, rcpW,
+                d1, d2, area);
+
+            subtriBase++;
+        }
+
+        v1 = v2;
+    }
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Util.inl b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Util.inl
new file mode 100644
index 0000000000000000000000000000000000000000..f8faeba7ba2d0634a80d92869b286d48d3071722
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/cudaraster/impl/Util.inl
@@ -0,0 +1,452 @@
+// Copyright (c) 2009-2022, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "PrivateDefs.hpp"
+
+namespace CR
+{
+//------------------------------------------------------------------------
+
+template<class T> __device__ __inline__ void swap(T& a, T& b)               { T t = a; a = b; b = t; }
+
+__device__ __inline__ U32   getLo                   (U64 a)                 { return __double2loint(__longlong_as_double(a)); }
+__device__ __inline__ S32   getLo                   (S64 a)                 { return __double2loint(__longlong_as_double(a)); }
+__device__ __inline__ U32   getHi                   (U64 a)                 { return __double2hiint(__longlong_as_double(a)); }
+__device__ __inline__ S32   getHi                   (S64 a)                 { return __double2hiint(__longlong_as_double(a)); }
+__device__ __inline__ U64   combineLoHi             (U32 lo, U32 hi)        { return __double_as_longlong(__hiloint2double(hi, lo)); }
+__device__ __inline__ S64   combineLoHi             (S32 lo, S32 hi)        { return __double_as_longlong(__hiloint2double(hi, lo)); }
+__device__ __inline__ U32   getLaneMaskLt           (void)                  { U32 r; asm("mov.u32 %0, %lanemask_lt;" : "=r"(r)); return r; }
+__device__ __inline__ U32   getLaneMaskLe           (void)                  { U32 r; asm("mov.u32 %0, %lanemask_le;" : "=r"(r)); return r; }
+__device__ __inline__ U32   getLaneMaskGt           (void)                  { U32 r; asm("mov.u32 %0, %lanemask_gt;" : "=r"(r)); return r; }
+__device__ __inline__ U32   getLaneMaskGe           (void)                  { U32 r; asm("mov.u32 %0, %lanemask_ge;" : "=r"(r)); return r; }
+__device__ __inline__ int   findLeadingOne          (U32 v)                 { U32 r; asm("bfind.u32 %0, %1;" : "=r"(r) : "r"(v)); return r; }
+__device__ __inline__ bool  singleLane              (void)                  { return ((::__ballot_sync(~0u, true) & getLaneMaskLt()) == 0); }
+
+__device__ __inline__ void  add_add_carry           (U32& rlo, U32 alo, U32 blo, U32& rhi, U32 ahi, U32 bhi) { U64 r = combineLoHi(alo, ahi) + combineLoHi(blo, bhi); rlo = getLo(r); rhi = getHi(r); }
+__device__ __inline__ S32   f32_to_s32_sat          (F32 a)                 { S32 v; asm("cvt.rni.sat.s32.f32 %0, %1;" : "=r"(v) : "f"(a)); return v; }
+__device__ __inline__ U32   f32_to_u32_sat          (F32 a)                 { U32 v; asm("cvt.rni.sat.u32.f32 %0, %1;" : "=r"(v) : "f"(a)); return v; }
+__device__ __inline__ U32   f32_to_u32_sat_rmi      (F32 a)                 { U32 v; asm("cvt.rmi.sat.u32.f32 %0, %1;" : "=r"(v) : "f"(a)); return v; }
+__device__ __inline__ U32   f32_to_u8_sat           (F32 a)                 { U32 v; asm("cvt.rni.sat.u8.f32 %0, %1;" : "=r"(v) : "f"(a)); return v; }
+__device__ __inline__ S64   f32_to_s64              (F32 a)                 { S64 v; asm("cvt.rni.s64.f32 %0, %1;" : "=l"(v) : "f"(a)); return v; }
+__device__ __inline__ S32   add_s16lo_s16lo			(S32 a, S32 b)			{ S32 v; asm("vadd.s32.s32.s32 %0, %1.h0, %2.h0;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   add_s16hi_s16lo			(S32 a, S32 b)			{ S32 v; asm("vadd.s32.s32.s32 %0, %1.h1, %2.h0;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   add_s16lo_s16hi			(S32 a, S32 b)			{ S32 v; asm("vadd.s32.s32.s32 %0, %1.h0, %2.h1;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   add_s16hi_s16hi			(S32 a, S32 b)			{ S32 v; asm("vadd.s32.s32.s32 %0, %1.h1, %2.h1;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_s16lo_s16lo			(S32 a, S32 b)			{ S32 v; asm("vsub.s32.s32.s32 %0, %1.h0, %2.h0;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_s16hi_s16lo			(S32 a, S32 b)			{ S32 v; asm("vsub.s32.s32.s32 %0, %1.h1, %2.h0;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_s16lo_s16hi			(S32 a, S32 b)			{ S32 v; asm("vsub.s32.s32.s32 %0, %1.h0, %2.h1;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_s16hi_s16hi			(S32 a, S32 b)			{ S32 v; asm("vsub.s32.s32.s32 %0, %1.h1, %2.h1;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_u16lo_u16lo			(U32 a, U32 b)			{ S32 v; asm("vsub.s32.u32.u32 %0, %1.h0, %2.h0;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_u16hi_u16lo			(U32 a, U32 b)			{ S32 v; asm("vsub.s32.u32.u32 %0, %1.h1, %2.h0;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_u16lo_u16hi			(U32 a, U32 b)			{ S32 v; asm("vsub.s32.u32.u32 %0, %1.h0, %2.h1;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ S32   sub_u16hi_u16hi			(U32 a, U32 b)			{ S32 v; asm("vsub.s32.u32.u32 %0, %1.h1, %2.h1;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ U32   add_b0					(U32 a, U32 b)			{ U32 v; asm("vadd.u32.u32.u32 %0, %1.b0, %2;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ U32   add_b1					(U32 a, U32 b)			{ U32 v; asm("vadd.u32.u32.u32 %0, %1.b1, %2;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ U32   add_b2					(U32 a, U32 b)			{ U32 v; asm("vadd.u32.u32.u32 %0, %1.b2, %2;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ U32   add_b3					(U32 a, U32 b)			{ U32 v; asm("vadd.u32.u32.u32 %0, %1.b3, %2;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ U32   vmad_b0					(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b0, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   vmad_b1					(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   vmad_b2					(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b2, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   vmad_b3					(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b3, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   vmad_b0_b3				(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b0, %2.b3, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   vmad_b1_b3				(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b1, %2.b3, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   vmad_b2_b3				(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b2, %2.b3, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   vmad_b3_b3				(U32 a, U32 b, U32 c)	{ U32 v; asm("vmad.u32.u32.u32 %0, %1.b3, %2.b3, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   add_mask8				(U32 a, U32 b)			{ U32 v; U32 z=0; asm("vadd.u32.u32.u32 %0.b0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(z)); return v; }
+__device__ __inline__ U32   sub_mask8				(U32 a, U32 b)			{ U32 v; U32 z=0; asm("vsub.u32.u32.u32 %0.b0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(z)); return v; }
+__device__ __inline__ S32   max_max					(S32 a, S32 b, S32 c)	{ S32 v; asm("vmax.s32.s32.s32.max %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ S32   min_min					(S32 a, S32 b, S32 c)	{ S32 v; asm("vmin.s32.s32.s32.min %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ S32   max_add					(S32 a, S32 b, S32 c)	{ S32 v; asm("vmax.s32.s32.s32.add %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ S32   min_add					(S32 a, S32 b, S32 c)	{ S32 v; asm("vmin.s32.s32.s32.add %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   add_add					(U32 a, U32 b, U32 c)	{ U32 v; asm("vadd.u32.u32.u32.add %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   sub_add					(U32 a, U32 b, U32 c)	{ U32 v; asm("vsub.u32.u32.u32.add %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   add_sub					(U32 a, U32 b, U32 c)	{ U32 v; asm("vsub.u32.u32.u32.add %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(c), "r"(b)); return v; }
+__device__ __inline__ S32   add_clamp_0_x			(S32 a, S32 b, S32 c)	{ S32 v; asm("vadd.u32.s32.s32.sat.min %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ S32   add_clamp_b0			(S32 a, S32 b, S32 c)	{ S32 v; asm("vadd.u32.s32.s32.sat %0.b0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ S32   add_clamp_b2			(S32 a, S32 b, S32 c)	{ S32 v; asm("vadd.u32.s32.s32.sat %0.b2, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ U32   prmt					(U32 a, U32 b, U32 c)   { U32 v; asm("prmt.b32 %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ S32   u32lo_sext              (U32 a)                 { U32 v; asm("cvt.s16.u32 %0, %1;" : "=r"(v) : "r"(a)); return v; }
+__device__ __inline__ U32   slct                    (U32 a, U32 b, S32 c)   { U32 v; asm("slct.u32.s32 %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ S32   slct                    (S32 a, S32 b, S32 c)   { S32 v; asm("slct.s32.s32 %0, %1, %2, %3;" : "=r"(v) : "r"(a), "r"(b), "r"(c)); return v; }
+__device__ __inline__ F32   slct                    (F32 a, F32 b, S32 c)   { F32 v; asm("slct.f32.s32 %0, %1, %2, %3;" : "=f"(v) : "f"(a), "f"(b), "r"(c)); return v; }
+__device__ __inline__ U32   isetge                  (S32 a, S32 b)          { U32 v; asm("set.ge.u32.s32 %0, %1, %2;" : "=r"(v) : "r"(a), "r"(b)); return v; }
+__device__ __inline__ F64   rcp_approx              (F64 a)                 { F64 v; asm("rcp.approx.ftz.f64 %0, %1;" : "=d"(v) : "d"(a)); return v; }
+__device__ __inline__ F32   fma_rm                  (F32 a, F32 b, F32 c)   { F32 v; asm("fma.rm.f32 %0, %1, %2, %3;" : "=f"(v) : "f"(a), "f"(b), "f"(c)); return v; }
+__device__ __inline__ U32   idiv_fast               (U32 a, U32 b);
+
+__device__ __inline__ uint3 setupPleq               (float3 values, int2 v0, int2 d1, int2 d2, F32 areaRcp);
+
+__device__ __inline__ void  cover8x8_setupLUT           (volatile U64* lut);
+__device__ __inline__ U64   cover8x8_exact_fast         (S32 ox, S32 oy, S32 dx, S32 dy, U32 flips, volatile const U64* lut); // Assumes viewport <= 2^11, subpixels <= 2^4, no guardband.
+__device__ __inline__ U64   cover8x8_lookupMask         (S64 yinit, U32 yinc, U32 flips, volatile const U64* lut);
+
+__device__ __inline__ U64   cover8x8_exact_noLUT        (S32 ox, S32 oy, S32 dx, S32 dy); // optimized reference implementation, does not require look-up table
+__device__ __inline__ U64   cover8x8_conservative_noLUT (S32 ox, S32 oy, S32 dx, S32 dy);
+__device__ __inline__ U64   cover8x8_generateMask_noLUT (S32 curr, S32 dx, S32 dy);
+
+template <class T> __device__ __inline__ void sortShared(T* ptr, int numItems); // Assumes that numItems <= threadsInBlock. Must sync before & after the call.
+
+__device__ __inline__ const CRImageParams& getImageParams(const CRParams& p, int idx)
+{
+    return (idx < CR_EMBED_IMAGE_PARAMS) ? p.imageParamsFirst[idx] : p.imageParamsExtra[idx - CR_EMBED_IMAGE_PARAMS];
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ int clipPolygonWithPlane(F32* baryOut, const F32* baryIn, int numIn, F32 v0, F32 v1, F32 v2)
+{
+    int numOut = 0;
+    if (numIn >= 3)
+    {
+        int ai = (numIn - 1) * 2;
+        F32 av = v0 + v1 * baryIn[ai + 0] + v2 * baryIn[ai + 1];
+        for (int bi = 0; bi < numIn * 2; bi += 2)
+        {
+            F32 bv = v0 + v1 * baryIn[bi + 0] + v2 * baryIn[bi + 1];
+            if (av * bv < 0.0f)
+            {
+                F32 bc = av / (av - bv);
+                F32 ac = 1.0f - bc;
+                baryOut[numOut + 0] = baryIn[ai + 0] * ac + baryIn[bi + 0] * bc;
+                baryOut[numOut + 1] = baryIn[ai + 1] * ac + baryIn[bi + 1] * bc;
+                numOut += 2;
+            }
+            if (bv >= 0.0f)
+            {
+                baryOut[numOut + 0] = baryIn[bi + 0];
+                baryOut[numOut + 1] = baryIn[bi + 1];
+                numOut += 2;
+            }
+            ai = bi;
+            av = bv;
+        }
+    }
+    return (numOut >> 1);
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ int clipTriangleWithFrustum(F32* bary, const F32* v0, const F32* v1, const F32* v2, const F32* d1, const F32* d2)
+{
+    int num = 3;
+    bary[0] = 0.0f, bary[1] = 0.0f;
+    bary[2] = 1.0f, bary[3] = 0.0f;
+    bary[4] = 0.0f, bary[5] = 1.0f;
+
+    if ((v0[3] < fabsf(v0[0])) | (v1[3] < fabsf(v1[0])) | (v2[3] < fabsf(v2[0])))
+    {
+        F32 temp[18];
+        num = clipPolygonWithPlane(temp, bary, num, v0[3] + v0[0], d1[3] + d1[0], d2[3] + d2[0]);
+        num = clipPolygonWithPlane(bary, temp, num, v0[3] - v0[0], d1[3] - d1[0], d2[3] - d2[0]);
+    }
+    if ((v0[3] < fabsf(v0[1])) | (v1[3] < fabsf(v1[1])) | (v2[3] < fabsf(v2[1])))
+    {
+        F32 temp[18];
+        num = clipPolygonWithPlane(temp, bary, num, v0[3] + v0[1], d1[3] + d1[1], d2[3] + d2[1]);
+        num = clipPolygonWithPlane(bary, temp, num, v0[3] - v0[1], d1[3] - d1[1], d2[3] - d2[1]);
+    }
+    if ((v0[3] < fabsf(v0[2])) | (v1[3] < fabsf(v1[2])) | (v2[3] < fabsf(v2[2])))
+    {
+        F32 temp[18];
+        num = clipPolygonWithPlane(temp, bary, num, v0[3] + v0[2], d1[3] + d1[2], d2[3] + d2[2]);
+        num = clipPolygonWithPlane(bary, temp, num, v0[3] - v0[2], d1[3] - d1[2], d2[3] - d2[2]);
+    }
+    return num;
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U32 idiv_fast(U32 a, U32 b)
+{
+    return f32_to_u32_sat_rmi(((F32)a + 0.5f) / (F32)b);
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U32 toABGR(float4 color)
+{
+	// 11 instructions: 4*FFMA, 4*F2I, 3*PRMT
+	U32 x = f32_to_u32_sat_rmi(fma_rm(color.x, (1 << 24) * 255.0f, (1 << 24) * 0.5f));
+	U32 y = f32_to_u32_sat_rmi(fma_rm(color.y, (1 << 24) * 255.0f, (1 << 24) * 0.5f));
+	U32 z = f32_to_u32_sat_rmi(fma_rm(color.z, (1 << 24) * 255.0f, (1 << 24) * 0.5f));
+	U32 w = f32_to_u32_sat_rmi(fma_rm(color.w, (1 << 24) * 255.0f, (1 << 24) * 0.5f));
+	return prmt(prmt(x, y, 0x0073), prmt(z, w, 0x0073), 0x5410);
+}
+
+//------------------------------------------------------------------------
+// v0 = subpixels relative to the bottom-left sampling point
+
+__device__ __inline__ uint3 setupPleq(float3 values, int2 v0, int2 d1, int2 d2, F32 areaRcp)
+{
+    F32 mx = fmaxf(fmaxf(values.x, values.y), values.z);
+    int sh = ::min(::max((__float_as_int(mx) >> 23) - (127 + 22), 0), 8);
+    S32 t0 = (U32)values.x >> sh;
+    S32 t1 = ((U32)values.y >> sh) - t0;
+    S32 t2 = ((U32)values.z >> sh) - t0;
+
+    U32 rcpMant = (__float_as_int(areaRcp) & 0x007FFFFF) | 0x00800000;
+    int rcpShift = (23 + 127) - (__float_as_int(areaRcp) >> 23);
+
+    uint3 pleq;
+    S64 xc = ((S64)t1 * d2.y - (S64)t2 * d1.y) * rcpMant;
+    S64 yc = ((S64)t2 * d1.x - (S64)t1 * d2.x) * rcpMant;
+    pleq.x = (U32)(xc >> (rcpShift - (sh + CR_SUBPIXEL_LOG2)));
+    pleq.y = (U32)(yc >> (rcpShift - (sh + CR_SUBPIXEL_LOG2)));
+
+    S32 centerX = (v0.x * 2 + min_min(d1.x, d2.x, 0) + max_max(d1.x, d2.x, 0)) >> (CR_SUBPIXEL_LOG2 + 1);
+    S32 centerY = (v0.y * 2 + min_min(d1.y, d2.y, 0) + max_max(d1.y, d2.y, 0)) >> (CR_SUBPIXEL_LOG2 + 1);
+    S32 vcx = v0.x - (centerX << CR_SUBPIXEL_LOG2);
+    S32 vcy = v0.y - (centerY << CR_SUBPIXEL_LOG2);
+
+    pleq.z = t0 << sh;
+    pleq.z -= (U32)(((xc >> 13) * vcx + (yc >> 13) * vcy) >> (rcpShift - (sh + 13)));
+    pleq.z -= pleq.x * centerX + pleq.y * centerY;
+    return pleq;
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ void cover8x8_setupLUT(volatile U64* lut)
+{
+    for (S32 lutIdx = threadIdx.x + blockDim.x * threadIdx.y; lutIdx < CR_COVER8X8_LUT_SIZE; lutIdx += blockDim.x * blockDim.y)
+    {
+        int half       = (lutIdx < (12 << 5)) ? 0 : 1;
+        int yint       = (lutIdx >> 5) - half * 12 - 3;
+        U32 shape      = ((lutIdx >> 2) & 7) << (31 - 2);
+        S32 slctSwapXY = lutIdx << (31 - 1);
+        S32 slctNegX   = lutIdx << (31 - 0);
+        S32 slctCompl  = slctSwapXY ^ slctNegX;
+
+        U64 mask = 0;
+        int xlo = half * 4;
+        int xhi = xlo + 4;
+        for (int x = xlo; x < xhi; x++)
+        {
+            int ylo = slct(0, ::max(yint, 0), slctCompl);
+            int yhi = slct(::min(yint, 8), 8, slctCompl);
+            for (int y = ylo; y < yhi; y++)
+            {
+                int xx = slct(x, y, slctSwapXY);
+                int yy = slct(y, x, slctSwapXY);
+                xx = slct(xx, 7 - xx, slctNegX);
+                mask |= (U64)1 << (xx + yy * 8);
+            }
+            yint += shape >> 31;
+            shape <<= 1;
+        }
+        lut[lutIdx] = mask;
+    }
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U64 cover8x8_exact_fast(S32 ox, S32 oy, S32 dx, S32 dy, U32 flips, volatile const U64* lut) // 52 instr
+{
+    F32  yinitBias  = (F32)(1 << (31 - CR_MAXVIEWPORT_LOG2 - CR_SUBPIXEL_LOG2 * 2));
+    F32  yinitScale = (F32)(1 << (32 - CR_SUBPIXEL_LOG2));
+    F32  yincScale  = 65536.0f * 65536.0f;
+
+    S32  slctFlipY  = flips << (31 - CR_FLIPBIT_FLIP_Y);
+    S32  slctFlipX  = flips << (31 - CR_FLIPBIT_FLIP_X);
+    S32  slctSwapXY = flips << (31 - CR_FLIPBIT_SWAP_XY);
+
+    // Evaluate cross product.
+
+    S32 t = ox * dy - oy * dx;
+    F32 det = (F32)slct(t, t - dy * (7 << CR_SUBPIXEL_LOG2), slctFlipX);
+    if (flips >= (1 << CR_FLIPBIT_COMPL))
+        det = -det;
+
+    // Represent Y as a function of X.
+
+    F32 xrcp  = 1.0f / (F32)::abs(slct(dx, dy, slctSwapXY));
+    F32 yzero = det * yinitScale * xrcp + yinitBias;
+    S64 yinit = f32_to_s64(slct(yzero, -yzero, slctFlipY));
+    U32 yinc  = f32_to_u32_sat((F32)::abs(slct(dy, dx, slctSwapXY)) * xrcp * yincScale);
+
+    // Lookup.
+
+    return cover8x8_lookupMask(yinit, yinc, flips, lut);
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U64 cover8x8_lookupMask(S64 yinit, U32 yinc, U32 flips, volatile const U64* lut)
+{
+    // First half.
+
+    U32 yfrac = getLo(yinit);
+    U32 shape = add_clamp_0_x(getHi(yinit) + 4, 0, 11);
+    add_add_carry(yfrac, yfrac, yinc, shape, shape, shape);
+    add_add_carry(yfrac, yfrac, yinc, shape, shape, shape);
+    add_add_carry(yfrac, yfrac, yinc, shape, shape, shape);
+    int oct = flips & ((1 << CR_FLIPBIT_FLIP_X) | (1 << CR_FLIPBIT_SWAP_XY));
+    U64 mask = *(U64*)((U8*)lut + oct + (shape << 5));
+
+    // Second half.
+
+    add_add_carry(yfrac, yfrac, yinc, shape, shape, shape);
+    shape = add_clamp_0_x(getHi(yinit) + 4, __popc(shape & 15), 11);
+    add_add_carry(yfrac, yfrac, yinc, shape, shape, shape);
+    add_add_carry(yfrac, yfrac, yinc, shape, shape, shape);
+    add_add_carry(yfrac, yfrac, yinc, shape, shape, shape);
+    mask |= *(U64*)((U8*)lut + oct + (shape << 5) + (12 << 8));
+    return (flips >= (1 << CR_FLIPBIT_COMPL)) ? ~mask : mask;
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U64 cover8x8_exact_noLUT(S32 ox, S32 oy, S32 dx, S32 dy)
+{
+    S32 curr = ox * dy - oy * dx;
+    if (dy > 0 || (dy == 0 && dx <= 0)) curr--; // exclusive
+    return cover8x8_generateMask_noLUT(curr, dx, dy);
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U64 cover8x8_conservative_noLUT(S32 ox, S32 oy, S32 dx, S32 dy)
+{
+    S32 curr = ox * dy - oy * dx;
+    if (dy > 0 || (dy == 0 && dx <= 0)) curr--; // exclusive
+    curr += (::abs(dx) + ::abs(dy)) << (CR_SUBPIXEL_LOG2 - 1);
+    return cover8x8_generateMask_noLUT(curr, dx, dy);
+}
+
+//------------------------------------------------------------------------
+
+__device__ __inline__ U64 cover8x8_generateMask_noLUT(S32 curr, S32 dx, S32 dy)
+{
+    curr += (dx - dy) * (7 << CR_SUBPIXEL_LOG2);
+    S32 stepX = dy << (CR_SUBPIXEL_LOG2 + 1);
+    S32 stepYorig = -dx - dy * 7;
+    S32 stepY = stepYorig << (CR_SUBPIXEL_LOG2 + 1);
+
+    U32 hi = isetge(curr, 0);
+    U32 frac = curr + curr;
+    for (int i = 62; i >= 32; i--)
+        add_add_carry(frac, frac, ((i & 7) == 7) ? stepY : stepX, hi, hi, hi);
+
+	U32 lo = 0;
+    for (int i = 31; i >= 0; i--)
+        add_add_carry(frac, frac, ((i & 7) == 7) ? stepY : stepX, lo, lo, lo);
+
+	lo ^= lo >> 1,  hi ^= hi >> 1;
+	lo ^= lo >> 2,  hi ^= hi >> 2;
+	lo ^= lo >> 4,  hi ^= hi >> 4;
+	lo ^= lo >> 8,  hi ^= hi >> 8;
+	lo ^= lo >> 16, hi ^= hi >> 16;
+
+	if (dy < 0)
+    {
+        lo ^= 0x55AA55AA;
+        hi ^= 0x55AA55AA;
+    }
+	if (stepYorig < 0)
+    {
+        lo ^= 0xFF00FF00;
+        hi ^= 0x00FF00FF;
+    }
+	if ((hi & 1) != 0)
+		lo = ~lo;
+
+    return combineLoHi(lo, hi);
+}
+
+//------------------------------------------------------------------------
+
+template <class T> __device__ __inline__ void sortShared(T* ptr, int numItems)
+{
+    int thrInBlock = threadIdx.x + threadIdx.y * blockDim.x;
+    int range = 16;
+
+    // Use transposition sort within each 16-wide subrange.
+
+    int base = thrInBlock * 2;
+    bool act = (base < numItems - 1);
+    U32 actMask = __ballot_sync(~0u, act);
+    if (act)
+    {
+        bool tryOdd = (base < numItems - 2 && (~base & (range - 2)) != 0);
+        T mid = ptr[base + 1];
+
+        for (int iter = 0; iter < range; iter += 2)
+        {
+            // Evens.
+
+            T tmp = ptr[base + 0];
+            if (tmp > mid)
+            {
+                ptr[base + 0] = mid;
+                mid = tmp;
+            }
+            __syncwarp(actMask);
+
+            // Odds.
+
+            if (tryOdd)
+            {
+                tmp = ptr[base + 2];
+                if (mid > tmp)
+                {
+                    ptr[base + 2] = mid;
+                    mid = tmp;
+                }
+            }
+            __syncwarp(actMask);
+        }
+        ptr[base + 1] = mid;
+    }
+
+    // Multiple subranges => Merge hierarchically.
+
+    for (; range < numItems; range <<= 1)
+    {
+        // Assuming that we would insert the current item into the other
+        // subrange, use binary search to find the appropriate slot.
+
+        __syncthreads();
+
+        T item;
+        int slot;
+        if (thrInBlock < numItems)
+        {
+            item = ptr[thrInBlock];
+            slot = (thrInBlock & -range) ^ range;
+            if (slot < numItems)
+            {
+                T tmp = ptr[slot];
+                bool inclusive = ((thrInBlock & range) != 0);
+                if (tmp < item || (inclusive && tmp == item))
+                {
+                    for (int step = (range >> 1); step != 0; step >>= 1)
+                    {
+                        int probe = slot + step;
+                        if (probe < numItems)
+                        {
+                            tmp = ptr[probe];
+                            if (tmp < item || (inclusive && tmp == item))
+                                slot = probe;
+                        }
+                    }
+                    slot++;
+                }
+            }
+        }
+
+        // Store the item at an appropriate place.
+
+        __syncthreads();
+
+        if (thrInBlock < numItems)
+            ptr[slot + (thrInBlock & (range * 2 - 1)) - range] = item;
+    }
+}
+
+//------------------------------------------------------------------------
+}
diff --git a/extensions/nvdiffrast/nvdiffrast/common/framework.h b/extensions/nvdiffrast/nvdiffrast/common/framework.h
new file mode 100644
index 0000000000000000000000000000000000000000..12d803caaf3210c45808dee41217c4c6c6edfe6e
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/framework.h
@@ -0,0 +1,49 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+
+// Framework-specific macros to enable code sharing.
+
+//------------------------------------------------------------------------
+// Tensorflow.
+
+#ifdef NVDR_TENSORFLOW
+#define EIGEN_USE_GPU
+#include "tensorflow/core/framework/op.h"
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/framework/shape_inference.h"
+#include "tensorflow/core/platform/default/logging.h"
+using namespace tensorflow;
+using namespace tensorflow::shape_inference;
+#define NVDR_CTX_ARGS OpKernelContext* _nvdr_ctx
+#define NVDR_CTX_PARAMS _nvdr_ctx
+#define NVDR_CHECK(COND, ERR) OP_REQUIRES(_nvdr_ctx, COND, errors::Internal(ERR))
+#define NVDR_CHECK_CUDA_ERROR(CUDA_CALL) OP_CHECK_CUDA_ERROR(_nvdr_ctx, CUDA_CALL)
+#define NVDR_CHECK_GL_ERROR(GL_CALL) OP_CHECK_GL_ERROR(_nvdr_ctx, GL_CALL)
+#endif
+
+//------------------------------------------------------------------------
+// PyTorch.
+
+#ifdef NVDR_TORCH
+#ifndef __CUDACC__
+#include <torch/extension.h>
+#include <ATen/cuda/CUDAContext.h>
+#include <ATen/cuda/CUDAUtils.h>
+#include <c10/cuda/CUDAGuard.h>
+#include <pybind11/numpy.h>
+#endif
+#define NVDR_CTX_ARGS int _nvdr_ctx_dummy
+#define NVDR_CTX_PARAMS 0
+#define NVDR_CHECK(COND, ERR) do { TORCH_CHECK(COND, ERR) } while(0)
+#define NVDR_CHECK_CUDA_ERROR(CUDA_CALL) do { cudaError_t err = CUDA_CALL; TORCH_CHECK(!err, "Cuda error: ", cudaGetLastError(), "[", #CUDA_CALL, ";]"); } while(0)
+#define NVDR_CHECK_GL_ERROR(GL_CALL) do { GL_CALL; GLenum err = glGetError(); TORCH_CHECK(err == GL_NO_ERROR, "OpenGL error: ", getGLErrorString(err), "[", #GL_CALL, ";]"); } while(0)
+#endif
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/glutil.cpp b/extensions/nvdiffrast/nvdiffrast/common/glutil.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..2af3e931b6808e2575d8a209d5485746499b3374
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/glutil.cpp
@@ -0,0 +1,403 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+// Common.
+//------------------------------------------------------------------------
+
+#include "framework.h"
+#include "glutil.h"
+#include <iostream>
+#include <iomanip>
+
+// Create the function pointers.
+#define GLUTIL_EXT(return_type, name, ...) return_type (GLAPIENTRY* name)(__VA_ARGS__) = 0;
+#include "glutil_extlist.h"
+#undef GLUTIL_EXT
+
+// Track initialization status.
+static volatile bool s_glExtInitialized = false;
+
+// Error strings.
+const char* getGLErrorString(GLenum err)
+{
+    switch(err)
+    {
+        case GL_NO_ERROR:                       return "GL_NO_ERROR";
+        case GL_INVALID_ENUM:                   return "GL_INVALID_ENUM";
+        case GL_INVALID_VALUE:                  return "GL_INVALID_VALUE";
+        case GL_INVALID_OPERATION:              return "GL_INVALID_OPERATION";
+        case GL_STACK_OVERFLOW:                 return "GL_STACK_OVERFLOW";
+        case GL_STACK_UNDERFLOW:                return "GL_STACK_UNDERFLOW";
+        case GL_OUT_OF_MEMORY:                  return "GL_OUT_OF_MEMORY";
+        case GL_INVALID_FRAMEBUFFER_OPERATION:  return "GL_INVALID_FRAMEBUFFER_OPERATION";
+        case GL_TABLE_TOO_LARGE:                return "GL_TABLE_TOO_LARGE";
+        case GL_CONTEXT_LOST:                   return "GL_CONTEXT_LOST";
+    }
+    return "Unknown error";
+}
+
+//------------------------------------------------------------------------
+// Windows.
+//------------------------------------------------------------------------
+
+#ifdef _WIN32
+
+static CRITICAL_SECTION getInitializedCriticalSection(void)
+{
+    CRITICAL_SECTION cs;
+    InitializeCriticalSection(&cs);
+    return cs;
+}
+
+static CRITICAL_SECTION s_getProcAddressMutex = getInitializedCriticalSection();
+
+static void safeGetProcAddress(const char* name, PROC* pfn)
+{
+    PROC result = wglGetProcAddress(name);
+    if (!result)
+    {
+        LeaveCriticalSection(&s_getProcAddressMutex); // Prepare for thread exit.
+        LOG(FATAL) << "wglGetProcAddress() failed for '" << name << "'";
+        exit(1); // Should never get here but make sure we exit.
+    }
+    *pfn = result;
+}
+
+static void initializeGLExtensions(void)
+{
+    // Use critical section for thread safety.
+    EnterCriticalSection(&s_getProcAddressMutex);
+
+    // Only dig function pointers if not done already.
+    if (!s_glExtInitialized)
+    {
+        // Generate code to populate the function pointers.
+#define GLUTIL_EXT(return_type, name, ...) safeGetProcAddress(#name, (PROC*)&name);
+#include "glutil_extlist.h"
+#undef GLUTIL_EXT
+
+        // Mark as initialized.
+        s_glExtInitialized = true;
+    }
+
+    // Done.
+    LeaveCriticalSection(&s_getProcAddressMutex);
+    return;
+}
+
+void setGLContext(GLContext& glctx)
+{
+    if (!glctx.hglrc)
+        LOG(FATAL) << "setGLContext() called with null gltcx";
+    if (!wglMakeCurrent(glctx.hdc, glctx.hglrc))
+        LOG(FATAL) << "wglMakeCurrent() failed when setting GL context";
+
+    if (glctx.extInitialized)
+        return;
+    initializeGLExtensions();
+    glctx.extInitialized = 1;
+}
+
+void releaseGLContext(void)
+{
+    if (!wglMakeCurrent(NULL, NULL))
+        LOG(FATAL) << "wglMakeCurrent() failed when releasing GL context";
+}
+
+extern "C" int set_gpu(const char*); // In setgpu.lib
+GLContext createGLContext(int cudaDeviceIdx)
+{
+    if (cudaDeviceIdx >= 0)
+    {
+        char pciBusId[256] = "";
+        LOG(INFO) << "Creating GL context for Cuda device " << cudaDeviceIdx;
+        if (cudaDeviceGetPCIBusId(pciBusId, 255, cudaDeviceIdx))
+        {
+            LOG(INFO) << "PCI bus id query failed";
+        }
+        else
+        {
+            int res = set_gpu(pciBusId);
+            LOG(INFO) << "Selecting device with PCI bus id " << pciBusId << " - " << (res ? "failed, expect crash or major slowdown" : "success");
+        }
+    }
+
+    HINSTANCE hInstance = GetModuleHandle(NULL);
+    WNDCLASS wc = {};
+    wc.style         = CS_OWNDC;
+    wc.lpfnWndProc   = DefWindowProc;
+    wc.hInstance     = hInstance;
+    wc.lpszClassName = "__DummyGLClassCPP";
+    int res = RegisterClass(&wc);
+
+    HWND hwnd = CreateWindow(
+        "__DummyGLClassCPP",        // lpClassName
+        "__DummyGLWindowCPP",       // lpWindowName
+        WS_OVERLAPPEDWINDOW,        // dwStyle
+        CW_USEDEFAULT,              // x
+        CW_USEDEFAULT,              // y
+        0, 0,                       // nWidth, nHeight
+        NULL, NULL,                 // hWndParent, hMenu
+        hInstance,                  // hInstance
+        NULL                        // lpParam
+    );
+
+    PIXELFORMATDESCRIPTOR pfd = {};
+    pfd.dwFlags      = PFD_SUPPORT_OPENGL;
+    pfd.iPixelType   = PFD_TYPE_RGBA;
+    pfd.iLayerType   = PFD_MAIN_PLANE;
+    pfd.cColorBits   = 32;
+    pfd.cDepthBits   = 24;
+    pfd.cStencilBits = 8;
+
+    HDC hdc = GetDC(hwnd);
+    int pixelformat = ChoosePixelFormat(hdc, &pfd);
+    SetPixelFormat(hdc, pixelformat, &pfd);
+
+    HGLRC hglrc = wglCreateContext(hdc);
+    LOG(INFO) << std::hex << std::setfill('0')
+              << "WGL OpenGL context created (hdc: 0x" << std::setw(8) << (uint32_t)(uintptr_t)hdc
+              << ", hglrc: 0x" << std::setw(8) << (uint32_t)(uintptr_t)hglrc << ")";
+
+    GLContext glctx = {hdc, hglrc, 0};
+    return glctx;
+}
+
+void destroyGLContext(GLContext& glctx)
+{
+    if (!glctx.hglrc)
+        LOG(FATAL) << "destroyGLContext() called with null gltcx";
+
+    // If this is the current context, release it.
+    if (wglGetCurrentContext() == glctx.hglrc)
+        releaseGLContext();
+
+    HWND hwnd = WindowFromDC(glctx.hdc);
+    if (!hwnd)
+        LOG(FATAL) << "WindowFromDC() failed";
+    if (!ReleaseDC(hwnd, glctx.hdc))
+        LOG(FATAL) << "ReleaseDC() failed";
+    if (!wglDeleteContext(glctx.hglrc))
+        LOG(FATAL) << "wglDeleteContext() failed";
+    if (!DestroyWindow(hwnd))
+        LOG(FATAL) << "DestroyWindow() failed";
+
+    LOG(INFO) << std::hex << std::setfill('0')
+              << "WGL OpenGL context destroyed (hdc: 0x" << std::setw(8) << (uint32_t)(uintptr_t)glctx.hdc
+              << ", hglrc: 0x" << std::setw(8) << (uint32_t)(uintptr_t)glctx.hglrc << ")";
+
+    memset(&glctx, 0, sizeof(GLContext));
+}
+
+#endif // _WIN32
+
+//------------------------------------------------------------------------
+// Linux.
+//------------------------------------------------------------------------
+
+#ifdef __linux__
+
+static pthread_mutex_t s_getProcAddressMutex;
+
+typedef void (*PROCFN)();
+
+static void safeGetProcAddress(const char* name, PROCFN* pfn)
+{
+    PROCFN result = eglGetProcAddress(name);
+    if (!result)
+    {
+        pthread_mutex_unlock(&s_getProcAddressMutex); // Prepare for thread exit.
+        LOG(FATAL) << "wglGetProcAddress() failed for '" << name << "'";
+        exit(1); // Should never get here but make sure we exit.
+    }
+    *pfn = result;
+}
+
+static void initializeGLExtensions(void)
+{
+    pthread_mutex_lock(&s_getProcAddressMutex);
+
+    // Only dig function pointers if not done already.
+    if (!s_glExtInitialized)
+    {
+        // Generate code to populate the function pointers.
+#define GLUTIL_EXT(return_type, name, ...) safeGetProcAddress(#name, (PROCFN*)&name);
+#include "glutil_extlist.h"
+#undef GLUTIL_EXT
+
+        // Mark as initialized.
+        s_glExtInitialized = true;
+    }
+
+    pthread_mutex_unlock(&s_getProcAddressMutex);
+    return;
+}
+
+void setGLContext(GLContext& glctx)
+{
+    if (!glctx.context)
+        LOG(FATAL) << "setGLContext() called with null gltcx";
+
+    if (!eglMakeCurrent(glctx.display, EGL_NO_SURFACE, EGL_NO_SURFACE, glctx.context))
+        LOG(ERROR) << "eglMakeCurrent() failed when setting GL context";
+
+    if (glctx.extInitialized)
+        return;
+    initializeGLExtensions();
+    glctx.extInitialized = 1;
+}
+
+void releaseGLContext(void)
+{
+    EGLDisplay display = eglGetCurrentDisplay();
+    if (display == EGL_NO_DISPLAY)
+        LOG(WARNING) << "releaseGLContext() called with no active display";
+    if (!eglMakeCurrent(display, EGL_NO_SURFACE, EGL_NO_SURFACE, EGL_NO_CONTEXT))
+        LOG(FATAL) << "eglMakeCurrent() failed when releasing GL context";
+}
+
+static EGLDisplay getCudaDisplay(int cudaDeviceIdx)
+{
+    typedef EGLBoolean (*eglQueryDevicesEXT_t)(EGLint, EGLDeviceEXT, EGLint*);
+    typedef EGLBoolean (*eglQueryDeviceAttribEXT_t)(EGLDeviceEXT, EGLint, EGLAttrib*);
+    typedef EGLDisplay (*eglGetPlatformDisplayEXT_t)(EGLenum, void*, const EGLint*);
+
+    eglQueryDevicesEXT_t eglQueryDevicesEXT = (eglQueryDevicesEXT_t)eglGetProcAddress("eglQueryDevicesEXT");
+    if (!eglQueryDevicesEXT)
+    {
+        LOG(INFO) << "eglGetProcAddress(\"eglQueryDevicesEXT\") failed";
+        return 0;
+    }
+
+    eglQueryDeviceAttribEXT_t eglQueryDeviceAttribEXT = (eglQueryDeviceAttribEXT_t)eglGetProcAddress("eglQueryDeviceAttribEXT");
+    if (!eglQueryDeviceAttribEXT)
+    {
+        LOG(INFO) << "eglGetProcAddress(\"eglQueryDeviceAttribEXT\") failed";
+        return 0;
+    }
+
+    eglGetPlatformDisplayEXT_t eglGetPlatformDisplayEXT = (eglGetPlatformDisplayEXT_t)eglGetProcAddress("eglGetPlatformDisplayEXT");
+    if (!eglGetPlatformDisplayEXT)
+    {
+        LOG(INFO) << "eglGetProcAddress(\"eglGetPlatformDisplayEXT\") failed";
+        return 0;
+    }
+
+    int num_devices = 0;
+    eglQueryDevicesEXT(0, 0, &num_devices);
+    if (!num_devices)
+        return 0;
+
+    EGLDisplay display = 0;
+    EGLDeviceEXT* devices = (EGLDeviceEXT*)malloc(num_devices * sizeof(void*));
+    eglQueryDevicesEXT(num_devices, devices, &num_devices);
+    for (int i=0; i < num_devices; i++)
+    {
+        EGLDeviceEXT device = devices[i];
+        intptr_t value = -1;
+        if (eglQueryDeviceAttribEXT(device, EGL_CUDA_DEVICE_NV, &value) && value == cudaDeviceIdx)
+        {
+            display = eglGetPlatformDisplayEXT(EGL_PLATFORM_DEVICE_EXT, device, 0);
+            break;
+        }
+    }
+
+    free(devices);
+    return display;
+}
+
+GLContext createGLContext(int cudaDeviceIdx)
+{
+    EGLDisplay display = 0;
+
+    if (cudaDeviceIdx >= 0)
+    {
+        char pciBusId[256] = "";
+        LOG(INFO) << "Creating GL context for Cuda device " << cudaDeviceIdx;
+        display = getCudaDisplay(cudaDeviceIdx);
+        if (!display)
+            LOG(INFO) << "Failed, falling back to default display";
+    }
+
+    if (!display)
+    {
+        display = eglGetDisplay(EGL_DEFAULT_DISPLAY);
+        if (display == EGL_NO_DISPLAY)
+            LOG(FATAL) << "eglGetDisplay() failed";
+    }
+
+    EGLint major;
+    EGLint minor;
+    if (!eglInitialize(display, &major, &minor))
+        LOG(FATAL) << "eglInitialize() failed";
+
+    // Choose configuration.
+
+    const EGLint context_attribs[] = {
+        EGL_RED_SIZE,           8,
+        EGL_GREEN_SIZE,         8,
+        EGL_BLUE_SIZE,          8,
+        EGL_ALPHA_SIZE,         8,
+        EGL_DEPTH_SIZE,         24,
+        EGL_STENCIL_SIZE,       8,
+        EGL_RENDERABLE_TYPE,    EGL_OPENGL_BIT,
+        EGL_SURFACE_TYPE,       EGL_PBUFFER_BIT,
+        EGL_NONE
+    };
+
+    EGLConfig config;
+    EGLint num_config;
+    if (!eglChooseConfig(display, context_attribs, &config, 1, &num_config))
+        LOG(FATAL) << "eglChooseConfig() failed";
+
+    // Create GL context.
+
+    if (!eglBindAPI(EGL_OPENGL_API))
+        LOG(FATAL) << "eglBindAPI() failed";
+
+    EGLContext context = eglCreateContext(display, config, EGL_NO_CONTEXT, NULL);
+    if (context == EGL_NO_CONTEXT)
+        LOG(FATAL) << "eglCreateContext() failed";
+
+    // Done.
+
+    LOG(INFO) << "EGL " << (int)minor << "." << (int)major << " OpenGL context created (disp: 0x"
+              << std::hex << std::setfill('0')
+              << std::setw(16) << (uintptr_t)display
+              << ", ctx: 0x" << std::setw(16) << (uintptr_t)context << ")";
+
+    GLContext glctx = {display, context, 0};
+    return glctx;
+}
+
+void destroyGLContext(GLContext& glctx)
+{
+    if (!glctx.context)
+        LOG(FATAL) << "destroyGLContext() called with null gltcx";
+
+    // If this is the current context, release it.
+    if (eglGetCurrentContext() == glctx.context)
+        releaseGLContext();
+
+    if (!eglDestroyContext(glctx.display, glctx.context))
+        LOG(ERROR) << "eglDestroyContext() failed";
+
+    LOG(INFO) << "EGL OpenGL context destroyed (disp: 0x"
+              << std::hex << std::setfill('0')
+              << std::setw(16) << (uintptr_t)glctx.display
+              << ", ctx: 0x" << std::setw(16) << (uintptr_t)glctx.context << ")";
+
+    memset(&glctx, 0, sizeof(GLContext));
+}
+
+//------------------------------------------------------------------------
+
+#endif // __linux__
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/glutil.h b/extensions/nvdiffrast/nvdiffrast/common/glutil.h
new file mode 100644
index 0000000000000000000000000000000000000000..e9a3a7d95a5af4a808a25097cc055b699024409e
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/glutil.h
@@ -0,0 +1,113 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+
+//------------------------------------------------------------------------
+// Windows-specific headers and types.
+//------------------------------------------------------------------------
+
+#ifdef _WIN32
+#define NOMINMAX
+#include <windows.h> // Required by gl.h in Windows.
+#define GLAPIENTRY APIENTRY
+
+struct GLContext
+{
+    HDC     hdc;
+    HGLRC   hglrc;
+    int     extInitialized;
+};
+
+#endif // _WIN32
+
+//------------------------------------------------------------------------
+// Linux-specific headers and types.
+//------------------------------------------------------------------------
+
+#ifdef __linux__
+#define EGL_NO_X11 // X11/Xlib.h has "#define Status int" which breaks Tensorflow. Avoid it.
+#define MESA_EGL_NO_X11_HEADERS
+#include <EGL/egl.h>
+#include <EGL/eglext.h>
+#define GLAPIENTRY
+
+struct GLContext
+{
+    EGLDisplay  display;
+    EGLContext  context;
+    int         extInitialized;
+};
+
+#endif // __linux__
+
+//------------------------------------------------------------------------
+// OpenGL, CUDA interop, GL extensions.
+//------------------------------------------------------------------------
+#define GL_GLEXT_LEGACY
+#include <GL/gl.h>
+#include <cuda_gl_interop.h>
+
+// Constants.
+#ifndef GL_VERSION_1_2
+#define GL_CLAMP_TO_EDGE                 0x812F
+#define GL_TEXTURE_3D                    0x806F
+#endif
+#ifndef GL_VERSION_1_5
+#define GL_ARRAY_BUFFER                  0x8892
+#define GL_DYNAMIC_DRAW                  0x88E8
+#define GL_ELEMENT_ARRAY_BUFFER          0x8893
+#endif
+#ifndef GL_VERSION_2_0
+#define GL_FRAGMENT_SHADER               0x8B30
+#define GL_INFO_LOG_LENGTH               0x8B84
+#define GL_LINK_STATUS                   0x8B82
+#define GL_VERTEX_SHADER                 0x8B31
+#endif
+#ifndef GL_VERSION_3_0
+#define GL_MAJOR_VERSION                 0x821B
+#define GL_MINOR_VERSION                 0x821C
+#define GL_RGBA32F                       0x8814
+#define GL_TEXTURE_2D_ARRAY              0x8C1A
+#endif
+#ifndef GL_VERSION_3_2
+#define GL_GEOMETRY_SHADER               0x8DD9
+#endif
+#ifndef GL_ARB_framebuffer_object
+#define GL_COLOR_ATTACHMENT0             0x8CE0
+#define GL_COLOR_ATTACHMENT1             0x8CE1
+#define GL_DEPTH_STENCIL                 0x84F9
+#define GL_DEPTH_STENCIL_ATTACHMENT      0x821A
+#define GL_DEPTH24_STENCIL8              0x88F0
+#define GL_FRAMEBUFFER                   0x8D40
+#define GL_INVALID_FRAMEBUFFER_OPERATION 0x0506
+#define GL_UNSIGNED_INT_24_8             0x84FA
+#endif
+#ifndef GL_ARB_imaging
+#define GL_TABLE_TOO_LARGE               0x8031
+#endif
+#ifndef GL_KHR_robustness
+#define GL_CONTEXT_LOST                  0x0507
+#endif
+
+// Declare function pointers to OpenGL extension functions.
+#define GLUTIL_EXT(return_type, name, ...) extern return_type (GLAPIENTRY* name)(__VA_ARGS__);
+#include "glutil_extlist.h"
+#undef GLUTIL_EXT
+
+//------------------------------------------------------------------------
+// Common functions.
+//------------------------------------------------------------------------
+
+void        setGLContext            (GLContext& glctx);
+void        releaseGLContext        (void);
+GLContext   createGLContext         (int cudaDeviceIdx);
+void        destroyGLContext        (GLContext& glctx);
+const char* getGLErrorString        (GLenum err);
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/glutil_extlist.h b/extensions/nvdiffrast/nvdiffrast/common/glutil_extlist.h
new file mode 100644
index 0000000000000000000000000000000000000000..afa08f399ad59e635b055548aec04cc661e28485
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/glutil_extlist.h
@@ -0,0 +1,48 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#ifndef GL_VERSION_1_2
+GLUTIL_EXT(void,   glTexImage3D,                GLenum target, GLint level, GLint internalFormat, GLsizei width, GLsizei height, GLsizei depth, GLint border, GLenum format, GLenum type, const void *pixels);
+#endif
+#ifndef GL_VERSION_1_5
+GLUTIL_EXT(void,   glBindBuffer,                GLenum target, GLuint buffer);
+GLUTIL_EXT(void,   glBufferData,                GLenum target, ptrdiff_t size, const void* data, GLenum usage);
+GLUTIL_EXT(void,   glGenBuffers,                GLsizei n, GLuint* buffers);
+#endif
+#ifndef GL_VERSION_2_0
+GLUTIL_EXT(void,   glAttachShader,              GLuint program, GLuint shader);
+GLUTIL_EXT(void,   glCompileShader,             GLuint shader);
+GLUTIL_EXT(GLuint, glCreateProgram,             void);
+GLUTIL_EXT(GLuint, glCreateShader,              GLenum type);
+GLUTIL_EXT(void,   glDrawBuffers,               GLsizei n, const GLenum* bufs);
+GLUTIL_EXT(void,   glEnableVertexAttribArray,   GLuint index);
+GLUTIL_EXT(void,   glGetProgramInfoLog,         GLuint program, GLsizei bufSize, GLsizei* length, char* infoLog);
+GLUTIL_EXT(void,   glGetProgramiv,              GLuint program, GLenum pname, GLint* param);
+GLUTIL_EXT(void,   glLinkProgram,               GLuint program);
+GLUTIL_EXT(void,   glShaderSource,              GLuint shader, GLsizei count, const char *const* string, const GLint* length);
+GLUTIL_EXT(void,   glUniform1f,                 GLint location, GLfloat v0);
+GLUTIL_EXT(void,   glUniform2f,                 GLint location, GLfloat v0, GLfloat v1);
+GLUTIL_EXT(void,   glUseProgram,                GLuint program);
+GLUTIL_EXT(void,   glVertexAttribPointer,       GLuint index, GLint size, GLenum type, GLboolean normalized, GLsizei stride, const void* pointer);
+#endif
+#ifndef GL_VERSION_3_2
+GLUTIL_EXT(void,   glFramebufferTexture,        GLenum target, GLenum attachment, GLuint texture, GLint level);
+#endif
+#ifndef GL_ARB_framebuffer_object
+GLUTIL_EXT(void,   glBindFramebuffer,           GLenum target, GLuint framebuffer);
+GLUTIL_EXT(void,   glGenFramebuffers,           GLsizei n, GLuint* framebuffers);
+#endif
+#ifndef GL_ARB_vertex_array_object
+GLUTIL_EXT(void,   glBindVertexArray,           GLuint array);
+GLUTIL_EXT(void,   glGenVertexArrays,           GLsizei n, GLuint* arrays);
+#endif
+#ifndef GL_ARB_multi_draw_indirect
+GLUTIL_EXT(void,   glMultiDrawElementsIndirect, GLenum mode, GLenum type, const void *indirect, GLsizei primcount, GLsizei stride);
+#endif
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/interpolate.cu b/extensions/nvdiffrast/nvdiffrast/common/interpolate.cu
new file mode 100644
index 0000000000000000000000000000000000000000..3bd2a7a7ab3111ae12f6cdce73906eeb9bbf6935
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/interpolate.cu
@@ -0,0 +1,276 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "common.h"
+#include "interpolate.h"
+
+//------------------------------------------------------------------------
+// Forward kernel.
+
+template <bool ENABLE_DA>
+static __forceinline__ __device__ void InterpolateFwdKernelTemplate(const InterpolateKernelParams p)
+{
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    if (px >= p.width || py >= p.height || pz >= p.depth)
+        return;
+
+    // Pixel index.
+    int pidx = px + p.width * (py + p.height * pz);
+
+    // Output ptrs.
+    float* out = p.out + pidx * p.numAttr;
+    float2* outDA = ENABLE_DA ? (((float2*)p.outDA) + pidx * p.numDiffAttr) : 0;
+
+    // Fetch rasterizer output.
+    float4 r = ((float4*)p.rast)[pidx];
+    int triIdx = float_to_triidx(r.w) - 1;
+    bool triValid = (triIdx >= 0 && triIdx < p.numTriangles);
+
+    // If no geometry in entire warp, zero the output and exit.
+    // Otherwise force barys to zero and output with live threads.
+    if (__all_sync(0xffffffffu, !triValid))
+    {
+        for (int i=0; i < p.numAttr; i++)
+            out[i] = 0.f;
+        if (ENABLE_DA)
+            for (int i=0; i < p.numDiffAttr; i++)
+                outDA[i] = make_float2(0.f, 0.f);
+        return;
+    }
+
+    // Fetch vertex indices.
+    int vi0 = triValid ? p.tri[triIdx * 3 + 0] : 0;
+    int vi1 = triValid ? p.tri[triIdx * 3 + 1] : 0;
+    int vi2 = triValid ? p.tri[triIdx * 3 + 2] : 0;
+
+    // Bail out if corrupt indices.
+    if (vi0 < 0 || vi0 >= p.numVertices ||
+        vi1 < 0 || vi1 >= p.numVertices ||
+        vi2 < 0 || vi2 >= p.numVertices)
+        return;
+
+    // In instance mode, adjust vertex indices by minibatch index unless broadcasting.
+    if (p.instance_mode && !p.attrBC)
+    {
+        vi0 += pz * p.numVertices;
+        vi1 += pz * p.numVertices;
+        vi2 += pz * p.numVertices;
+    }
+
+    // Pointers to attributes.
+    const float* a0 = p.attr + vi0 * p.numAttr;
+    const float* a1 = p.attr + vi1 * p.numAttr;
+    const float* a2 = p.attr + vi2 * p.numAttr;
+
+    // Barys. If no triangle, force all to zero -> output is zero.
+    float b0 = triValid ? r.x : 0.f;
+    float b1 = triValid ? r.y : 0.f;
+    float b2 = triValid ? (1.f - r.x - r.y) : 0.f;
+
+    // Interpolate and write attributes.
+    for (int i=0; i < p.numAttr; i++)
+        out[i] = b0*a0[i] + b1*a1[i] + b2*a2[i];
+
+    // No diff attrs? Exit.
+    if (!ENABLE_DA)
+        return;
+
+    // Read bary pixel differentials if we have a triangle.
+    float4 db = make_float4(0.f, 0.f, 0.f, 0.f);
+    if (triValid)
+        db = ((float4*)p.rastDB)[pidx];
+
+    // Unpack a bit.
+    float dudx = db.x;
+    float dudy = db.y;
+    float dvdx = db.z;
+    float dvdy = db.w;
+
+    // Calculate the pixel differentials of chosen attributes.    
+    for (int i=0; i < p.numDiffAttr; i++)
+    {   
+        // Input attribute index.
+        int j = p.diff_attrs_all ? i : p.diffAttrs[i];
+        if (j < 0)
+            j += p.numAttr; // Python-style negative indices.
+
+        // Zero output if invalid index.
+        float dsdx = 0.f;
+        float dsdy = 0.f;
+        if (j >= 0 && j < p.numAttr)
+        {
+            float s0 = a0[j];
+            float s1 = a1[j];
+            float s2 = a2[j];
+            float dsdu = s0 - s2;
+            float dsdv = s1 - s2;
+            dsdx = dudx*dsdu + dvdx*dsdv;
+            dsdy = dudy*dsdu + dvdy*dsdv;
+        }
+
+        // Write.
+        outDA[i] = make_float2(dsdx, dsdy);
+    }
+}
+
+// Template specializations.
+__global__ void InterpolateFwdKernel  (const InterpolateKernelParams p) { InterpolateFwdKernelTemplate<false>(p); }
+__global__ void InterpolateFwdKernelDa(const InterpolateKernelParams p) { InterpolateFwdKernelTemplate<true>(p); }
+
+//------------------------------------------------------------------------
+// Gradient kernel.
+
+template <bool ENABLE_DA>
+static __forceinline__ __device__ void InterpolateGradKernelTemplate(const InterpolateKernelParams p)
+{
+    // Temporary space for coalesced atomics.
+    CA_DECLARE_TEMP(IP_GRAD_MAX_KERNEL_BLOCK_WIDTH * IP_GRAD_MAX_KERNEL_BLOCK_HEIGHT);
+
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    if (px >= p.width || py >= p.height || pz >= p.depth)
+        return;
+
+    // Pixel index.
+    int pidx = px + p.width * (py + p.height * pz);
+
+    // Fetch triangle ID. If none, output zero bary/db gradients and exit.
+    float4 r = ((float4*)p.rast)[pidx];
+    int triIdx = float_to_triidx(r.w) - 1;
+    if (triIdx < 0 || triIdx >= p.numTriangles)
+    {
+        ((float4*)p.gradRaster)[pidx] = make_float4(0.f, 0.f, 0.f, 0.f);
+        if (ENABLE_DA)
+            ((float4*)p.gradRasterDB)[pidx] = make_float4(0.f, 0.f, 0.f, 0.f);
+        return;
+    }
+
+    // Fetch vertex indices.
+    int vi0 = p.tri[triIdx * 3 + 0];
+    int vi1 = p.tri[triIdx * 3 + 1];
+    int vi2 = p.tri[triIdx * 3 + 2];
+
+    // Bail out if corrupt indices.
+    if (vi0 < 0 || vi0 >= p.numVertices ||
+        vi1 < 0 || vi1 >= p.numVertices ||
+        vi2 < 0 || vi2 >= p.numVertices)
+        return;
+
+    // In instance mode, adjust vertex indices by minibatch index unless broadcasting.
+    if (p.instance_mode && !p.attrBC)
+    {
+        vi0 += pz * p.numVertices;
+        vi1 += pz * p.numVertices;
+        vi2 += pz * p.numVertices;
+    }
+
+    // Initialize coalesced atomics.
+    CA_SET_GROUP(triIdx);
+
+    // Pointers to inputs.
+    const float* a0 = p.attr + vi0 * p.numAttr;
+    const float* a1 = p.attr + vi1 * p.numAttr;
+    const float* a2 = p.attr + vi2 * p.numAttr;
+    const float* pdy = p.dy + pidx * p.numAttr;
+
+    // Pointers to outputs.
+    float* ga0 = p.gradAttr + vi0 * p.numAttr;
+    float* ga1 = p.gradAttr + vi1 * p.numAttr;
+    float* ga2 = p.gradAttr + vi2 * p.numAttr;
+
+    // Barys and bary gradient accumulators.
+    float b0 = r.x;
+    float b1 = r.y;
+    float b2 = 1.f - r.x - r.y;
+    float gb0 = 0.f;
+    float gb1 = 0.f;
+
+    // Loop over attributes and accumulate attribute gradients.
+    for (int i=0; i < p.numAttr; i++)
+    {
+        float y = pdy[i];
+        float s0 = a0[i];
+        float s1 = a1[i];
+        float s2 = a2[i];
+        gb0 += y * (s0 - s2);
+        gb1 += y * (s1 - s2);
+        caAtomicAdd(ga0 + i, b0 * y);
+        caAtomicAdd(ga1 + i, b1 * y);
+        caAtomicAdd(ga2 + i, b2 * y);
+    }
+
+    // Write the bary gradients.
+    ((float4*)p.gradRaster)[pidx] = make_float4(gb0, gb1, 0.f, 0.f);
+
+    // If pixel differentials disabled, we're done.
+    if (!ENABLE_DA)
+        return;
+
+    // Calculate gradients based on attribute pixel differentials.
+    const float2* dda = ((float2*)p.dda) + pidx * p.numDiffAttr;
+    float gdudx = 0.f;
+    float gdudy = 0.f;
+    float gdvdx = 0.f;
+    float gdvdy = 0.f;
+
+    // Read bary pixel differentials.
+    float4 db = ((float4*)p.rastDB)[pidx];
+    float dudx = db.x;
+    float dudy = db.y;
+    float dvdx = db.z;
+    float dvdy = db.w;
+
+    for (int i=0; i < p.numDiffAttr; i++)
+    {
+        // Input attribute index.
+        int j = p.diff_attrs_all ? i : p.diffAttrs[i];
+        if (j < 0)
+            j += p.numAttr; // Python-style negative indices.
+
+        // Check that index is valid.
+        if (j >= 0 && j < p.numAttr)
+        {
+            float2 dsdxy = dda[i];
+            float dsdx = dsdxy.x;
+            float dsdy = dsdxy.y;
+
+            float s0 = a0[j];
+            float s1 = a1[j];
+            float s2 = a2[j];
+
+            // Gradients of db.
+            float dsdu = s0 - s2;
+            float dsdv = s1 - s2;
+            gdudx += dsdu * dsdx;
+            gdudy += dsdu * dsdy;
+            gdvdx += dsdv * dsdx;
+            gdvdy += dsdv * dsdy;
+
+            // Gradients of attributes.
+            float du = dsdx*dudx + dsdy*dudy;
+            float dv = dsdx*dvdx + dsdy*dvdy;
+            caAtomicAdd(ga0 + j, du);
+            caAtomicAdd(ga1 + j, dv);
+            caAtomicAdd(ga2 + j, -du - dv);
+        }
+    }
+
+    // Write.
+    ((float4*)p.gradRasterDB)[pidx] = make_float4(gdudx, gdudy, gdvdx, gdvdy);
+}
+
+// Template specializations.
+__global__ void InterpolateGradKernel  (const InterpolateKernelParams p) { InterpolateGradKernelTemplate<false>(p); }
+__global__ void InterpolateGradKernelDa(const InterpolateKernelParams p) { InterpolateGradKernelTemplate<true>(p); }
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/interpolate.h b/extensions/nvdiffrast/nvdiffrast/common/interpolate.h
new file mode 100644
index 0000000000000000000000000000000000000000..d35d8388240e97c255c837446609d8ae00cd78d9
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/interpolate.h
@@ -0,0 +1,49 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+
+//------------------------------------------------------------------------
+// Constants and helpers.
+
+#define IP_FWD_MAX_KERNEL_BLOCK_WIDTH   8
+#define IP_FWD_MAX_KERNEL_BLOCK_HEIGHT  8
+#define IP_GRAD_MAX_KERNEL_BLOCK_WIDTH  8
+#define IP_GRAD_MAX_KERNEL_BLOCK_HEIGHT 8
+#define IP_MAX_DIFF_ATTRS               32
+
+//------------------------------------------------------------------------
+// CUDA kernel params.
+
+struct InterpolateKernelParams
+{
+    const int*      tri;                            // Incoming triangle buffer.
+    const float*    attr;                           // Incoming attribute buffer.
+    const float*    rast;                           // Incoming rasterizer output buffer.
+    const float*    rastDB;                         // Incoming rasterizer output buffer for bary derivatives.
+    const float*    dy;                             // Incoming attribute gradients.
+    const float*    dda;                            // Incoming attr diff gradients.
+    float*          out;                            // Outgoing interpolated attributes.
+    float*          outDA;                          // Outgoing texcoord major axis lengths.
+    float*          gradAttr;                       // Outgoing attribute gradients.
+    float*          gradRaster;                     // Outgoing rasterizer gradients.
+    float*          gradRasterDB;                   // Outgoing rasterizer bary diff gradients.
+    int             numTriangles;                   // Number of triangles.
+    int             numVertices;                    // Number of vertices.
+    int             numAttr;                        // Number of total vertex attributes.
+    int             numDiffAttr;                    // Number of attributes to differentiate.
+    int             width;                          // Image width.
+    int             height;                         // Image height.
+    int             depth;                          // Minibatch size.
+    int             attrBC;                         // 0=normal, 1=attr is broadcast.
+    int             instance_mode;                  // 0=normal, 1=instance mode.
+    int             diff_attrs_all;                 // 0=normal, 1=produce pixel differentials for all attributes.
+    int             diffAttrs[IP_MAX_DIFF_ATTRS];   // List of attributes to differentiate.
+};
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/rasterize.cu b/extensions/nvdiffrast/nvdiffrast/common/rasterize.cu
new file mode 100644
index 0000000000000000000000000000000000000000..455aca3e09064d1fbe25b406ff958ad8efb4dffe
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/rasterize.cu
@@ -0,0 +1,276 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "common.h"
+#include "rasterize.h"
+
+//------------------------------------------------------------------------
+// Cuda forward rasterizer pixel shader kernel.
+
+__global__ void RasterizeCudaFwdShaderKernel(const RasterizeCudaFwdShaderParams p)
+{
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    if (px >= p.width_out || py >= p.height_out || pz >= p.depth)
+        return;
+
+    // Pixel indices.
+    int pidx_in  = px + p.width_in  * (py + p.height_in  * pz);
+    int pidx_out = px + p.width_out * (py + p.height_out * pz);
+
+    // Fetch triangle idx.
+    int triIdx = p.in_idx[pidx_in] - 1;
+    if (triIdx < 0 || triIdx >= p.numTriangles)
+    {
+        // No or corrupt triangle.
+        ((float4*)p.out)[pidx_out] = make_float4(0.0, 0.0, 0.0, 0.0); // Clear out.
+        ((float4*)p.out_db)[pidx_out] = make_float4(0.0, 0.0, 0.0, 0.0); // Clear out_db.
+        return;
+    }
+
+    // Fetch vertex indices.
+    int vi0 = p.tri[triIdx * 3 + 0];
+    int vi1 = p.tri[triIdx * 3 + 1];
+    int vi2 = p.tri[triIdx * 3 + 2];
+
+    // Bail out if vertex indices are corrupt.
+    if (vi0 < 0 || vi0 >= p.numVertices ||
+        vi1 < 0 || vi1 >= p.numVertices ||
+        vi2 < 0 || vi2 >= p.numVertices)
+        return;
+
+    // In instance mode, adjust vertex indices by minibatch index.
+    if (p.instance_mode)
+    {
+        vi0 += pz * p.numVertices;
+        vi1 += pz * p.numVertices;
+        vi2 += pz * p.numVertices;
+    }
+
+    // Fetch vertex positions.
+    float4 p0 = ((float4*)p.pos)[vi0];
+    float4 p1 = ((float4*)p.pos)[vi1];
+    float4 p2 = ((float4*)p.pos)[vi2];
+
+    // Evaluate edge functions.
+    float fx = p.xs * (float)px + p.xo;
+    float fy = p.ys * (float)py + p.yo;
+    float p0x = p0.x - fx * p0.w;
+    float p0y = p0.y - fy * p0.w;
+    float p1x = p1.x - fx * p1.w;
+    float p1y = p1.y - fy * p1.w;
+    float p2x = p2.x - fx * p2.w;
+    float p2y = p2.y - fy * p2.w;
+    float a0 = p1x*p2y - p1y*p2x;
+    float a1 = p2x*p0y - p2y*p0x;
+    float a2 = p0x*p1y - p0y*p1x;
+
+    // Perspective correct, normalized barycentrics.
+    float iw = 1.f / (a0 + a1 + a2);
+    float b0 = a0 * iw;
+    float b1 = a1 * iw;
+
+    // Compute z/w for depth buffer.
+    float z = p0.z * a0 + p1.z * a1 + p2.z * a2;
+    float w = p0.w * a0 + p1.w * a1 + p2.w * a2;
+    float zw = z / w;
+
+    // Clamps to avoid NaNs.
+    b0 = __saturatef(b0); // Clamp to [+0.0, 1.0].
+    b1 = __saturatef(b1); // Clamp to [+0.0, 1.0].
+    zw = fmaxf(fminf(zw, 1.f), -1.f);
+
+    // Emit output.
+    ((float4*)p.out)[pidx_out] = make_float4(b0, b1, zw, triidx_to_float(triIdx + 1));
+
+    // Calculate bary pixel differentials.
+    float dfxdx = p.xs * iw;
+    float dfydy = p.ys * iw;
+    float da0dx = p2.y*p1.w - p1.y*p2.w;
+    float da0dy = p1.x*p2.w - p2.x*p1.w;
+    float da1dx = p0.y*p2.w - p2.y*p0.w;
+    float da1dy = p2.x*p0.w - p0.x*p2.w;
+    float da2dx = p1.y*p0.w - p0.y*p1.w;
+    float da2dy = p0.x*p1.w - p1.x*p0.w;
+    float datdx = da0dx + da1dx + da2dx;
+    float datdy = da0dy + da1dy + da2dy;
+    float dudx = dfxdx * (b0 * datdx - da0dx);
+    float dudy = dfydy * (b0 * datdy - da0dy);
+    float dvdx = dfxdx * (b1 * datdx - da1dx);
+    float dvdy = dfydy * (b1 * datdy - da1dy);
+
+    // Emit bary pixel differentials.
+    ((float4*)p.out_db)[pidx_out] = make_float4(dudx, dudy, dvdx, dvdy);
+}
+
+//------------------------------------------------------------------------
+// Gradient Cuda kernel.
+
+template <bool ENABLE_DB>
+static __forceinline__ __device__ void RasterizeGradKernelTemplate(const RasterizeGradParams p)
+{
+    // Temporary space for coalesced atomics.
+    CA_DECLARE_TEMP(RAST_GRAD_MAX_KERNEL_BLOCK_WIDTH * RAST_GRAD_MAX_KERNEL_BLOCK_HEIGHT);
+
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    if (px >= p.width || py >= p.height || pz >= p.depth)
+        return;
+
+    // Pixel index.
+    int pidx = px + p.width * (py + p.height * pz);
+
+    // Read triangle idx and dy.
+    float2 dy  = ((float2*)p.dy)[pidx * 2];
+    float4 ddb = ENABLE_DB ? ((float4*)p.ddb)[pidx] : make_float4(0.f, 0.f, 0.f, 0.f);
+    int triIdx = float_to_triidx(((float*)p.out)[pidx * 4 + 3]) - 1;
+
+    // Exit if nothing to do.
+    if (triIdx < 0 || triIdx >= p.numTriangles)
+        return; // No or corrupt triangle.
+    int grad_all_dy = __float_as_int(dy.x) | __float_as_int(dy.y); // Bitwise OR of all incoming gradients.
+    int grad_all_ddb = 0;
+    if (ENABLE_DB)
+        grad_all_ddb = __float_as_int(ddb.x) | __float_as_int(ddb.y) | __float_as_int(ddb.z) | __float_as_int(ddb.w);
+    if (((grad_all_dy | grad_all_ddb) << 1) == 0)
+        return; // All incoming gradients are +0/-0.
+
+    // Fetch vertex indices.
+    int vi0 = p.tri[triIdx * 3 + 0];
+    int vi1 = p.tri[triIdx * 3 + 1];
+    int vi2 = p.tri[triIdx * 3 + 2];
+
+    // Bail out if vertex indices are corrupt.
+    if (vi0 < 0 || vi0 >= p.numVertices ||
+        vi1 < 0 || vi1 >= p.numVertices ||
+        vi2 < 0 || vi2 >= p.numVertices)
+        return;
+
+    // In instance mode, adjust vertex indices by minibatch index.
+    if (p.instance_mode)
+    {
+        vi0 += pz * p.numVertices;
+        vi1 += pz * p.numVertices;
+        vi2 += pz * p.numVertices;
+    }
+
+    // Initialize coalesced atomics.
+    CA_SET_GROUP(triIdx);
+
+    // Fetch vertex positions.
+    float4 p0 = ((float4*)p.pos)[vi0];
+    float4 p1 = ((float4*)p.pos)[vi1];
+    float4 p2 = ((float4*)p.pos)[vi2];
+
+    // Evaluate edge functions.
+    float fx = p.xs * (float)px + p.xo;
+    float fy = p.ys * (float)py + p.yo;
+    float p0x = p0.x - fx * p0.w;
+    float p0y = p0.y - fy * p0.w;
+    float p1x = p1.x - fx * p1.w;
+    float p1y = p1.y - fy * p1.w;
+    float p2x = p2.x - fx * p2.w;
+    float p2y = p2.y - fy * p2.w;
+    float a0 = p1x*p2y - p1y*p2x;
+    float a1 = p2x*p0y - p2y*p0x;
+    float a2 = p0x*p1y - p0y*p1x;
+
+    // Compute inverse area with epsilon.
+    float at = a0 + a1 + a2;
+    float ep = copysignf(1e-6f, at); // ~1 pixel in 1k x 1k image.
+    float iw = 1.f / (at + ep);
+
+    // Perspective correct, normalized barycentrics.
+    float b0 = a0 * iw;
+    float b1 = a1 * iw;
+
+    // Position gradients.
+    float gb0  = dy.x * iw;
+    float gb1  = dy.y * iw;
+    float gbb  = gb0 * b0 + gb1 * b1;
+    float gp0x = gbb * (p2y - p1y) - gb1 * p2y;
+    float gp1x = gbb * (p0y - p2y) + gb0 * p2y;
+    float gp2x = gbb * (p1y - p0y) - gb0 * p1y + gb1 * p0y;
+    float gp0y = gbb * (p1x - p2x) + gb1 * p2x;
+    float gp1y = gbb * (p2x - p0x) - gb0 * p2x;
+    float gp2y = gbb * (p0x - p1x) + gb0 * p1x - gb1 * p0x;
+    float gp0w = -fx * gp0x - fy * gp0y;
+    float gp1w = -fx * gp1x - fy * gp1y;
+    float gp2w = -fx * gp2x - fy * gp2y;
+
+    // Bary differential gradients.
+    if (ENABLE_DB && ((grad_all_ddb) << 1) != 0)
+    {
+        float dfxdX = p.xs * iw;
+        float dfydY = p.ys * iw;
+        ddb.x *= dfxdX;
+        ddb.y *= dfydY;
+        ddb.z *= dfxdX;
+        ddb.w *= dfydY;
+
+        float da0dX = p1.y * p2.w - p2.y * p1.w;
+        float da1dX = p2.y * p0.w - p0.y * p2.w;
+        float da2dX = p0.y * p1.w - p1.y * p0.w;
+        float da0dY = p2.x * p1.w - p1.x * p2.w;
+        float da1dY = p0.x * p2.w - p2.x * p0.w;
+        float da2dY = p1.x * p0.w - p0.x * p1.w;
+        float datdX = da0dX + da1dX + da2dX;
+        float datdY = da0dY + da1dY + da2dY;
+
+        float x01 = p0.x - p1.x;
+        float x12 = p1.x - p2.x;
+        float x20 = p2.x - p0.x;
+        float y01 = p0.y - p1.y;
+        float y12 = p1.y - p2.y;
+        float y20 = p2.y - p0.y;
+        float w01 = p0.w - p1.w;
+        float w12 = p1.w - p2.w;
+        float w20 = p2.w - p0.w;
+
+        float a0p1 = fy * p2.x - fx * p2.y;
+        float a0p2 = fx * p1.y - fy * p1.x;
+        float a1p0 = fx * p2.y - fy * p2.x;
+        float a1p2 = fy * p0.x - fx * p0.y;
+
+        float wdudX = 2.f * b0 * datdX - da0dX;
+        float wdudY = 2.f * b0 * datdY - da0dY;
+        float wdvdX = 2.f * b1 * datdX - da1dX;
+        float wdvdY = 2.f * b1 * datdY - da1dY;
+
+        float c0  = iw * (ddb.x * wdudX + ddb.y * wdudY + ddb.z * wdvdX + ddb.w * wdvdY);
+        float cx  = c0 * fx - ddb.x * b0 - ddb.z * b1;
+        float cy  = c0 * fy - ddb.y * b0 - ddb.w * b1;
+        float cxy = iw * (ddb.x * datdX + ddb.y * datdY);
+        float czw = iw * (ddb.z * datdX + ddb.w * datdY);
+
+        gp0x += c0 * y12 - cy * w12              + czw * p2y                                               + ddb.w * p2.w;
+        gp1x += c0 * y20 - cy * w20 - cxy * p2y                              - ddb.y * p2.w;
+        gp2x += c0 * y01 - cy * w01 + cxy * p1y  - czw * p0y                 + ddb.y * p1.w                - ddb.w * p0.w;
+        gp0y += cx * w12 - c0 * x12              - czw * p2x                                - ddb.z * p2.w;
+        gp1y += cx * w20 - c0 * x20 + cxy * p2x               + ddb.x * p2.w;
+        gp2y += cx * w01 - c0 * x01 - cxy * p1x  + czw * p0x  - ddb.x * p1.w                + ddb.z * p0.w;
+        gp0w += cy * x12 - cx * y12              - czw * a1p0                               + ddb.z * p2.y - ddb.w * p2.x;
+        gp1w += cy * x20 - cx * y20 - cxy * a0p1              - ddb.x * p2.y + ddb.y * p2.x;
+        gp2w += cy * x01 - cx * y01 - cxy * a0p2 - czw * a1p2 + ddb.x * p1.y - ddb.y * p1.x - ddb.z * p0.y + ddb.w * p0.x;
+    }
+
+    // Accumulate using coalesced atomics.
+    caAtomicAdd3_xyw(p.grad + 4 * vi0, gp0x, gp0y, gp0w);
+    caAtomicAdd3_xyw(p.grad + 4 * vi1, gp1x, gp1y, gp1w);
+    caAtomicAdd3_xyw(p.grad + 4 * vi2, gp2x, gp2y, gp2w);
+}
+
+// Template specializations.
+__global__ void RasterizeGradKernel  (const RasterizeGradParams p) { RasterizeGradKernelTemplate<false>(p); }
+__global__ void RasterizeGradKernelDb(const RasterizeGradParams p) { RasterizeGradKernelTemplate<true>(p); }
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/rasterize.h b/extensions/nvdiffrast/nvdiffrast/common/rasterize.h
new file mode 100644
index 0000000000000000000000000000000000000000..cb3104fae0e533e6da134e01c6020f70effb4964
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/rasterize.h
@@ -0,0 +1,60 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+
+//------------------------------------------------------------------------
+// Constants and helpers.
+
+#define RAST_CUDA_FWD_SHADER_KERNEL_BLOCK_WIDTH  8
+#define RAST_CUDA_FWD_SHADER_KERNEL_BLOCK_HEIGHT 8
+#define RAST_GRAD_MAX_KERNEL_BLOCK_WIDTH  8
+#define RAST_GRAD_MAX_KERNEL_BLOCK_HEIGHT 8
+
+//------------------------------------------------------------------------
+// CUDA forward rasterizer shader kernel params.
+
+struct RasterizeCudaFwdShaderParams
+{
+    const float*    pos;            // Vertex positions.
+    const int*      tri;            // Triangle indices.
+    const int*      in_idx;         // Triangle idx buffer from rasterizer.
+    float*          out;            // Main output buffer.
+    float*          out_db;         // Bary pixel gradient output buffer.
+    int             numTriangles;   // Number of triangles.
+    int             numVertices;    // Number of vertices.
+    int             width_in;       // Input image width.
+    int             height_in;      // Input image height.
+    int             width_out;      // Output image width.
+    int             height_out;     // Output image height.
+    int             depth;          // Size of minibatch.
+    int             instance_mode;  // 1 if in instance rendering mode.
+    float           xs, xo, ys, yo; // Pixel position to clip-space x, y transform.
+};
+
+//------------------------------------------------------------------------
+// Gradient CUDA kernel params.
+
+struct RasterizeGradParams
+{
+    const float*    pos;            // Incoming position buffer.
+    const int*      tri;            // Incoming triangle buffer.
+    const float*    out;            // Rasterizer output buffer.
+    const float*    dy;             // Incoming gradients of rasterizer output buffer.
+    const float*    ddb;            // Incoming gradients of bary diff output buffer.
+    float*          grad;           // Outgoing position gradients.
+    int             numTriangles;   // Number of triangles.
+    int             numVertices;    // Number of vertices.
+    int             width;          // Image width.
+    int             height;         // Image height.
+    int             depth;          // Size of minibatch.
+    int             instance_mode;  // 1 if in instance rendering mode.
+    float           xs, xo, ys, yo; // Pixel position to clip-space x, y transform.
+};
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/rasterize_gl.cpp b/extensions/nvdiffrast/nvdiffrast/common/rasterize_gl.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..ac71ccd8eb91740c4c8cacc21cb9fb00f452403c
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/rasterize_gl.cpp
@@ -0,0 +1,644 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "rasterize_gl.h"
+#include "glutil.h"
+#include <vector>
+#define STRINGIFY_SHADER_SOURCE(x) #x
+
+//------------------------------------------------------------------------
+// Helpers.
+
+#define ROUND_UP(x, y) ((((x) + ((y) - 1)) / (y)) * (y))
+static int ROUND_UP_BITS(uint32_t x, uint32_t y)
+{
+    // Round x up so that it has at most y bits of mantissa.
+    if (x < (1u << y))
+        return x;
+    uint32_t m = 0;
+    while (x & ~m)
+        m = (m << 1) | 1u;
+    m >>= y;
+    if (!(x & m))
+        return x;
+    return (x | m) + 1u;
+}
+
+//------------------------------------------------------------------------
+// Draw command struct used by rasterizer.
+
+struct GLDrawCmd
+{
+    uint32_t    count;
+    uint32_t    instanceCount;
+    uint32_t    firstIndex;
+    uint32_t    baseVertex;
+    uint32_t    baseInstance;
+};
+
+//------------------------------------------------------------------------
+// GL helpers.
+
+static void compileGLShader(NVDR_CTX_ARGS, const RasterizeGLState& s, GLuint* pShader, GLenum shaderType, const char* src_buf)
+{
+    std::string src(src_buf);
+
+    // Set preprocessor directives.
+    int n = src.find('\n') + 1; // After first line containing #version directive.
+    if (s.enableZModify)
+        src.insert(n, "#define IF_ZMODIFY(x) x\n");
+    else
+        src.insert(n, "#define IF_ZMODIFY(x)\n");
+
+    const char *cstr = src.c_str();
+    *pShader = 0;
+    NVDR_CHECK_GL_ERROR(*pShader = glCreateShader(shaderType));
+    NVDR_CHECK_GL_ERROR(glShaderSource(*pShader, 1, &cstr, 0));
+    NVDR_CHECK_GL_ERROR(glCompileShader(*pShader));
+}
+
+static void constructGLProgram(NVDR_CTX_ARGS, GLuint* pProgram, GLuint glVertexShader, GLuint glGeometryShader, GLuint glFragmentShader)
+{
+    *pProgram = 0;
+
+    GLuint glProgram = 0;
+    NVDR_CHECK_GL_ERROR(glProgram = glCreateProgram());
+    NVDR_CHECK_GL_ERROR(glAttachShader(glProgram, glVertexShader));
+    NVDR_CHECK_GL_ERROR(glAttachShader(glProgram, glGeometryShader));
+    NVDR_CHECK_GL_ERROR(glAttachShader(glProgram, glFragmentShader));
+    NVDR_CHECK_GL_ERROR(glLinkProgram(glProgram));
+
+    GLint linkStatus = 0;
+    NVDR_CHECK_GL_ERROR(glGetProgramiv(glProgram, GL_LINK_STATUS, &linkStatus));
+    if (!linkStatus)
+    {
+        GLint infoLen = 0;
+        NVDR_CHECK_GL_ERROR(glGetProgramiv(glProgram, GL_INFO_LOG_LENGTH, &infoLen));
+        if (infoLen)
+        {
+            const char* hdr = "glLinkProgram() failed:\n";
+            std::vector<char> info(strlen(hdr) + infoLen);
+            strcpy(&info[0], hdr);
+            NVDR_CHECK_GL_ERROR(glGetProgramInfoLog(glProgram, infoLen, &infoLen, &info[strlen(hdr)]));
+            NVDR_CHECK(0, &info[0]);
+        }
+        NVDR_CHECK(0, "glLinkProgram() failed");
+    }
+
+    *pProgram = glProgram;
+}
+
+//------------------------------------------------------------------------
+// Shared C++ functions.
+
+void rasterizeInitGLContext(NVDR_CTX_ARGS, RasterizeGLState& s, int cudaDeviceIdx)
+{
+    // Create GL context and set it current.
+    s.glctx = createGLContext(cudaDeviceIdx);
+    setGLContext(s.glctx);
+
+    // Version check.
+    GLint vMajor = 0;
+    GLint vMinor = 0;
+    glGetIntegerv(GL_MAJOR_VERSION, &vMajor);
+    glGetIntegerv(GL_MINOR_VERSION, &vMinor);
+    glGetError(); // Clear possible GL_INVALID_ENUM error in version query.
+    LOG(INFO) << "OpenGL version reported as " << vMajor << "." << vMinor;
+    NVDR_CHECK((vMajor == 4 && vMinor >= 4) || vMajor > 4, "OpenGL 4.4 or later is required");
+
+    // Enable depth modification workaround on A100 and later.
+    int capMajor = 0;
+    NVDR_CHECK_CUDA_ERROR(cudaDeviceGetAttribute(&capMajor, cudaDevAttrComputeCapabilityMajor, cudaDeviceIdx));
+    s.enableZModify = (capMajor >= 8);
+
+    // Number of output buffers.
+    int num_outputs = s.enableDB ? 2 : 1;
+
+    // Set up vertex shader.
+    compileGLShader(NVDR_CTX_PARAMS, s, &s.glVertexShader, GL_VERTEX_SHADER,
+        "#version 330\n"
+        "#extension GL_ARB_shader_draw_parameters : enable\n"
+        STRINGIFY_SHADER_SOURCE(
+            layout(location = 0) in vec4 in_pos;
+            out int v_layer;
+            out int v_offset;
+            void main()
+            {
+                int layer = gl_DrawIDARB;
+                gl_Position = in_pos;
+                v_layer = layer;
+                v_offset = gl_BaseInstanceARB; // Sneak in TriID offset here.
+            }
+        )
+    );
+
+    // Geometry and fragment shaders depend on if bary differential output is enabled or not.
+    if (s.enableDB)
+    {
+        // Set up geometry shader. Calculation of per-pixel bary differentials is based on:
+        //           u = (u/w) / (1/w)
+        //   --> du/dX = d((u/w) / (1/w))/dX
+        //   --> du/dX = [d(u/w)/dX - u*d(1/w)/dX] * w
+        // and we know both d(u/w)/dX and d(1/w)/dX are constant over triangle.
+        compileGLShader(NVDR_CTX_PARAMS, s, &s.glGeometryShader, GL_GEOMETRY_SHADER,
+            "#version 430\n"
+            STRINGIFY_SHADER_SOURCE(
+                layout(triangles) in;
+                layout(triangle_strip, max_vertices=3) out;
+                layout(location = 0) uniform vec2 vp_scale;
+                in int v_layer[];
+                in int v_offset[];
+                out vec4 var_uvzw;
+                out vec4 var_db;
+                void main()
+                {
+                    // Plane equations for bary differentials.
+                    float w0 = gl_in[0].gl_Position.w;
+                    float w1 = gl_in[1].gl_Position.w;
+                    float w2 = gl_in[2].gl_Position.w;
+                    vec2 p0 = gl_in[0].gl_Position.xy;
+                    vec2 p1 = gl_in[1].gl_Position.xy;
+                    vec2 p2 = gl_in[2].gl_Position.xy;
+                    vec2 e0 = p0*w2 - p2*w0;
+                    vec2 e1 = p1*w2 - p2*w1;
+                    float a = e0.x*e1.y - e0.y*e1.x;
+
+                    // Clamp area to an epsilon to avoid arbitrarily high bary differentials.
+                    float eps = 1e-6f; // ~1 pixel in 1k x 1k image.
+                    float ca = (abs(a) >= eps) ? a : (a < 0.f) ? -eps : eps; // Clamp with sign.
+                    float ia = 1.f / ca; // Inverse area.
+
+                    vec2 ascl = ia * vp_scale;
+                    float dudx =  e1.y * ascl.x;
+                    float dudy = -e1.x * ascl.y;
+                    float dvdx = -e0.y * ascl.x;
+                    float dvdy =  e0.x * ascl.y;
+
+                    float duwdx = w2 * dudx;
+                    float dvwdx = w2 * dvdx;
+                    float duvdx = w0 * dudx + w1 * dvdx;
+                    float duwdy = w2 * dudy;
+                    float dvwdy = w2 * dvdy;
+                    float duvdy = w0 * dudy + w1 * dvdy;
+
+                    vec4 db0 = vec4(duvdx - dvwdx, duvdy - dvwdy, dvwdx, dvwdy);
+                    vec4 db1 = vec4(duwdx, duwdy, duvdx - duwdx, duvdy - duwdy);
+                    vec4 db2 = vec4(duwdx, duwdy, dvwdx, dvwdy);
+
+                    int layer_id = v_layer[0];
+                    int prim_id = gl_PrimitiveIDIn + v_offset[0];
+
+                    gl_Layer = layer_id; gl_PrimitiveID = prim_id; gl_Position = vec4(gl_in[0].gl_Position.x, gl_in[0].gl_Position.y, gl_in[0].gl_Position.z, gl_in[0].gl_Position.w); var_uvzw = vec4(1.f, 0.f, gl_in[0].gl_Position.z, gl_in[0].gl_Position.w); var_db = db0; EmitVertex();
+                    gl_Layer = layer_id; gl_PrimitiveID = prim_id; gl_Position = vec4(gl_in[1].gl_Position.x, gl_in[1].gl_Position.y, gl_in[1].gl_Position.z, gl_in[1].gl_Position.w); var_uvzw = vec4(0.f, 1.f, gl_in[1].gl_Position.z, gl_in[1].gl_Position.w); var_db = db1; EmitVertex();
+                    gl_Layer = layer_id; gl_PrimitiveID = prim_id; gl_Position = vec4(gl_in[2].gl_Position.x, gl_in[2].gl_Position.y, gl_in[2].gl_Position.z, gl_in[2].gl_Position.w); var_uvzw = vec4(0.f, 0.f, gl_in[2].gl_Position.z, gl_in[2].gl_Position.w); var_db = db2; EmitVertex();
+                }
+            )
+        );
+
+        // Set up fragment shader.
+        compileGLShader(NVDR_CTX_PARAMS, s, &s.glFragmentShader, GL_FRAGMENT_SHADER,
+            "#version 430\n"
+            STRINGIFY_SHADER_SOURCE(
+                in vec4 var_uvzw;
+                in vec4 var_db;
+                layout(location = 0) out vec4 out_raster;
+                layout(location = 1) out vec4 out_db;
+                IF_ZMODIFY(
+                    layout(location = 1) uniform float in_dummy;
+                )
+                void main()
+                {
+                    int id_int = gl_PrimitiveID + 1;
+                    float id_float = (id_int <= 0x01000000) ? float(id_int) : intBitsToFloat(0x4a800000 + id_int);
+
+                    out_raster = vec4(var_uvzw.x, var_uvzw.y, var_uvzw.z / var_uvzw.w, id_float);
+                    out_db = var_db * var_uvzw.w;
+                    IF_ZMODIFY(gl_FragDepth = gl_FragCoord.z + in_dummy;)
+                }
+            )
+        );
+
+        // Set up fragment shader for depth peeling.
+        compileGLShader(NVDR_CTX_PARAMS, s, &s.glFragmentShaderDP, GL_FRAGMENT_SHADER,
+            "#version 430\n"
+            STRINGIFY_SHADER_SOURCE(
+                in vec4 var_uvzw;
+                in vec4 var_db;
+                layout(binding = 0) uniform sampler2DArray out_prev;
+                layout(location = 0) out vec4 out_raster;
+                layout(location = 1) out vec4 out_db;
+                IF_ZMODIFY(
+                    layout(location = 1) uniform float in_dummy;
+                )
+                void main()
+                {
+                    int id_int = gl_PrimitiveID + 1;
+                    float id_float = (id_int <= 0x01000000) ? float(id_int) : intBitsToFloat(0x4a800000 + id_int);
+
+                    vec4 prev = texelFetch(out_prev, ivec3(gl_FragCoord.x, gl_FragCoord.y, gl_Layer), 0);
+                    float depth_new = var_uvzw.z / var_uvzw.w;
+                    if (prev.w == 0 || depth_new <= prev.z)
+                        discard;
+                    out_raster = vec4(var_uvzw.x, var_uvzw.y, depth_new, id_float);
+                    out_db = var_db * var_uvzw.w;
+                    IF_ZMODIFY(gl_FragDepth = gl_FragCoord.z + in_dummy;)
+                }
+            )
+        );
+    }
+    else
+    {
+        // Geometry shader without bary differential output.
+        compileGLShader(NVDR_CTX_PARAMS, s, &s.glGeometryShader, GL_GEOMETRY_SHADER,
+            "#version 330\n"
+            STRINGIFY_SHADER_SOURCE(
+                layout(triangles) in;
+                layout(triangle_strip, max_vertices=3) out;
+                in int v_layer[];
+                in int v_offset[];
+                out vec4 var_uvzw;
+                void main()
+                {
+                    int layer_id = v_layer[0];
+                    int prim_id = gl_PrimitiveIDIn + v_offset[0];
+
+                    gl_Layer = layer_id; gl_PrimitiveID = prim_id; gl_Position = vec4(gl_in[0].gl_Position.x, gl_in[0].gl_Position.y, gl_in[0].gl_Position.z, gl_in[0].gl_Position.w); var_uvzw = vec4(1.f, 0.f, gl_in[0].gl_Position.z, gl_in[0].gl_Position.w); EmitVertex();
+                    gl_Layer = layer_id; gl_PrimitiveID = prim_id; gl_Position = vec4(gl_in[1].gl_Position.x, gl_in[1].gl_Position.y, gl_in[1].gl_Position.z, gl_in[1].gl_Position.w); var_uvzw = vec4(0.f, 1.f, gl_in[1].gl_Position.z, gl_in[1].gl_Position.w); EmitVertex();
+                    gl_Layer = layer_id; gl_PrimitiveID = prim_id; gl_Position = vec4(gl_in[2].gl_Position.x, gl_in[2].gl_Position.y, gl_in[2].gl_Position.z, gl_in[2].gl_Position.w); var_uvzw = vec4(0.f, 0.f, gl_in[2].gl_Position.z, gl_in[2].gl_Position.w); EmitVertex();
+                }
+            )
+        );
+
+        // Fragment shader without bary differential output.
+        compileGLShader(NVDR_CTX_PARAMS, s, &s.glFragmentShader, GL_FRAGMENT_SHADER,
+            "#version 430\n"
+            STRINGIFY_SHADER_SOURCE(
+                in vec4 var_uvzw;
+                layout(location = 0) out vec4 out_raster;
+                IF_ZMODIFY(
+                    layout(location = 1) uniform float in_dummy;
+                )
+                void main()
+                {
+                    int id_int = gl_PrimitiveID + 1;
+                    float id_float = (id_int <= 0x01000000) ? float(id_int) : intBitsToFloat(0x4a800000 + id_int);
+
+                    out_raster = vec4(var_uvzw.x, var_uvzw.y, var_uvzw.z / var_uvzw.w, id_float);
+                    IF_ZMODIFY(gl_FragDepth = gl_FragCoord.z + in_dummy;)
+                }
+            )
+        );
+
+        // Depth peeling variant of fragment shader.
+        compileGLShader(NVDR_CTX_PARAMS, s, &s.glFragmentShaderDP, GL_FRAGMENT_SHADER,
+            "#version 430\n"
+            STRINGIFY_SHADER_SOURCE(
+                in vec4 var_uvzw;
+                layout(binding = 0) uniform sampler2DArray out_prev;
+                layout(location = 0) out vec4 out_raster;
+                IF_ZMODIFY(
+                    layout(location = 1) uniform float in_dummy;
+                )
+                void main()
+                {
+                    int id_int = gl_PrimitiveID + 1;
+                    float id_float = (id_int <= 0x01000000) ? float(id_int) : intBitsToFloat(0x4a800000 + id_int);
+
+                    vec4 prev = texelFetch(out_prev, ivec3(gl_FragCoord.x, gl_FragCoord.y, gl_Layer), 0);
+                    float depth_new = var_uvzw.z / var_uvzw.w;
+                    if (prev.w == 0 || depth_new <= prev.z)
+                        discard;
+                    out_raster = vec4(var_uvzw.x, var_uvzw.y, var_uvzw.z / var_uvzw.w, id_float);
+                    IF_ZMODIFY(gl_FragDepth = gl_FragCoord.z + in_dummy;)
+                }
+            )
+        );
+    }
+
+    // Finalize programs.
+    constructGLProgram(NVDR_CTX_PARAMS, &s.glProgram, s.glVertexShader, s.glGeometryShader, s.glFragmentShader);
+    constructGLProgram(NVDR_CTX_PARAMS, &s.glProgramDP, s.glVertexShader, s.glGeometryShader, s.glFragmentShaderDP);
+
+    // Construct main fbo and bind permanently.
+    NVDR_CHECK_GL_ERROR(glGenFramebuffers(1, &s.glFBO));
+    NVDR_CHECK_GL_ERROR(glBindFramebuffer(GL_FRAMEBUFFER, s.glFBO));
+
+    // Enable two color attachments.
+    GLenum draw_buffers[2] = { GL_COLOR_ATTACHMENT0, GL_COLOR_ATTACHMENT1 };
+    NVDR_CHECK_GL_ERROR(glDrawBuffers(num_outputs, draw_buffers));
+
+    // Construct vertex array object.
+    NVDR_CHECK_GL_ERROR(glGenVertexArrays(1, &s.glVAO));
+    NVDR_CHECK_GL_ERROR(glBindVertexArray(s.glVAO));
+
+    // Construct position buffer, bind permanently, enable, set ptr.
+    NVDR_CHECK_GL_ERROR(glGenBuffers(1, &s.glPosBuffer));
+    NVDR_CHECK_GL_ERROR(glBindBuffer(GL_ARRAY_BUFFER, s.glPosBuffer));
+    NVDR_CHECK_GL_ERROR(glEnableVertexAttribArray(0));
+    NVDR_CHECK_GL_ERROR(glVertexAttribPointer(0, 4, GL_FLOAT, GL_FALSE, 0, 0));
+
+    // Construct index buffer and bind permanently.
+    NVDR_CHECK_GL_ERROR(glGenBuffers(1, &s.glTriBuffer));
+    NVDR_CHECK_GL_ERROR(glBindBuffer(GL_ELEMENT_ARRAY_BUFFER, s.glTriBuffer));
+
+    // Set up depth test.
+    NVDR_CHECK_GL_ERROR(glEnable(GL_DEPTH_TEST));
+    NVDR_CHECK_GL_ERROR(glDepthFunc(GL_LESS));
+    NVDR_CHECK_GL_ERROR(glClearDepth(1.0));
+
+    // Create and bind output buffers. Storage is allocated later.
+    NVDR_CHECK_GL_ERROR(glGenTextures(num_outputs, s.glColorBuffer));
+    for (int i=0; i < num_outputs; i++)
+    {
+        NVDR_CHECK_GL_ERROR(glBindTexture(GL_TEXTURE_2D_ARRAY, s.glColorBuffer[i]));
+        NVDR_CHECK_GL_ERROR(glFramebufferTexture(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0 + i, s.glColorBuffer[i], 0));
+    }
+
+    // Create and bind depth/stencil buffer. Storage is allocated later.
+    NVDR_CHECK_GL_ERROR(glGenTextures(1, &s.glDepthStencilBuffer));
+    NVDR_CHECK_GL_ERROR(glBindTexture(GL_TEXTURE_2D_ARRAY, s.glDepthStencilBuffer));
+    NVDR_CHECK_GL_ERROR(glFramebufferTexture(GL_FRAMEBUFFER, GL_DEPTH_STENCIL_ATTACHMENT, s.glDepthStencilBuffer, 0));
+
+    // Create texture name for previous output buffer (depth peeling).
+    NVDR_CHECK_GL_ERROR(glGenTextures(1, &s.glPrevOutBuffer));
+}
+
+void rasterizeResizeBuffers(NVDR_CTX_ARGS, RasterizeGLState& s, bool& changes, int posCount, int triCount, int width, int height, int depth)
+{
+    changes = false;
+
+    // Resize vertex buffer?
+    if (posCount > s.posCount)
+    {
+        if (s.cudaPosBuffer)
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaPosBuffer));
+        s.posCount = (posCount > 64) ? ROUND_UP_BITS(posCount, 2) : 64;
+        LOG(INFO) << "Increasing position buffer size to " << s.posCount << " float32";
+        NVDR_CHECK_GL_ERROR(glBufferData(GL_ARRAY_BUFFER, s.posCount * sizeof(float), NULL, GL_DYNAMIC_DRAW));
+        NVDR_CHECK_CUDA_ERROR(cudaGraphicsGLRegisterBuffer(&s.cudaPosBuffer, s.glPosBuffer, cudaGraphicsRegisterFlagsWriteDiscard));
+        changes = true;
+    }
+
+    // Resize triangle buffer?
+    if (triCount > s.triCount)
+    {
+        if (s.cudaTriBuffer)
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaTriBuffer));
+        s.triCount = (triCount > 64) ? ROUND_UP_BITS(triCount, 2) : 64;
+        LOG(INFO) << "Increasing triangle buffer size to " << s.triCount << " int32";
+        NVDR_CHECK_GL_ERROR(glBufferData(GL_ELEMENT_ARRAY_BUFFER, s.triCount * sizeof(int32_t), NULL, GL_DYNAMIC_DRAW));
+        NVDR_CHECK_CUDA_ERROR(cudaGraphicsGLRegisterBuffer(&s.cudaTriBuffer, s.glTriBuffer, cudaGraphicsRegisterFlagsWriteDiscard));
+        changes = true;
+    }
+
+    // Resize framebuffer?
+    if (width > s.width || height > s.height || depth > s.depth)
+    {
+        int num_outputs = s.enableDB ? 2 : 1;
+        if (s.cudaColorBuffer[0])
+            for (int i=0; i < num_outputs; i++)
+                NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaColorBuffer[i]));
+
+        if (s.cudaPrevOutBuffer)
+        {
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaPrevOutBuffer));
+            s.cudaPrevOutBuffer = 0;
+        }
+
+        // New framebuffer size.
+        s.width  = (width > s.width) ? width : s.width;
+        s.height = (height > s.height) ? height : s.height;
+        s.depth  = (depth > s.depth) ? depth : s.depth;
+        s.width  = ROUND_UP(s.width, 32);
+        s.height = ROUND_UP(s.height, 32);
+        LOG(INFO) << "Increasing frame buffer size to (width, height, depth) = (" << s.width << ", " << s.height << ", " << s.depth << ")";
+
+        // Allocate color buffers.
+        for (int i=0; i < num_outputs; i++)
+        {
+            NVDR_CHECK_GL_ERROR(glBindTexture(GL_TEXTURE_2D_ARRAY, s.glColorBuffer[i]));
+            NVDR_CHECK_GL_ERROR(glTexImage3D(GL_TEXTURE_2D_ARRAY, 0, GL_RGBA32F, s.width, s.height, s.depth, 0, GL_RGBA, GL_UNSIGNED_BYTE, 0));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_MAG_FILTER, GL_NEAREST));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_MIN_FILTER, GL_NEAREST));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_WRAP_S, GL_CLAMP_TO_EDGE));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_WRAP_T, GL_CLAMP_TO_EDGE));
+        }
+
+        // Allocate depth/stencil buffer.
+        NVDR_CHECK_GL_ERROR(glBindTexture(GL_TEXTURE_2D_ARRAY, s.glDepthStencilBuffer));
+        NVDR_CHECK_GL_ERROR(glTexImage3D(GL_TEXTURE_2D_ARRAY, 0, GL_DEPTH24_STENCIL8, s.width, s.height, s.depth, 0, GL_DEPTH_STENCIL, GL_UNSIGNED_INT_24_8, 0));
+
+        // (Re-)register all GL buffers into Cuda.
+        for (int i=0; i < num_outputs; i++)
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsGLRegisterImage(&s.cudaColorBuffer[i], s.glColorBuffer[i], GL_TEXTURE_3D, cudaGraphicsRegisterFlagsReadOnly));
+
+        changes = true;
+    }
+}
+
+void rasterizeRender(NVDR_CTX_ARGS, RasterizeGLState& s, cudaStream_t stream, const float* posPtr, int posCount, int vtxPerInstance, const int32_t* triPtr, int triCount, const int32_t* rangesPtr, int width, int height, int depth, int peeling_idx)
+{
+    // Only copy inputs if we are on first iteration of depth peeling or not doing it at all.
+    if (peeling_idx < 1)
+    {
+        if (triPtr)
+        {
+            // Copy both position and triangle buffers.
+            void* glPosPtr = NULL;
+            void* glTriPtr = NULL;
+            size_t posBytes = 0;
+            size_t triBytes = 0;
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsMapResources(2, &s.cudaPosBuffer, stream));
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsResourceGetMappedPointer(&glPosPtr, &posBytes, s.cudaPosBuffer));
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsResourceGetMappedPointer(&glTriPtr, &triBytes, s.cudaTriBuffer));
+            NVDR_CHECK(posBytes >= posCount * sizeof(float), "mapped GL position buffer size mismatch");
+            NVDR_CHECK(triBytes >= triCount * sizeof(int32_t), "mapped GL triangle buffer size mismatch");
+            NVDR_CHECK_CUDA_ERROR(cudaMemcpyAsync(glPosPtr, posPtr, posCount * sizeof(float), cudaMemcpyDeviceToDevice, stream));
+            NVDR_CHECK_CUDA_ERROR(cudaMemcpyAsync(glTriPtr, triPtr, triCount * sizeof(int32_t), cudaMemcpyDeviceToDevice, stream));
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnmapResources(2, &s.cudaPosBuffer, stream));
+        }
+        else
+        {
+            // Copy position buffer only. Triangles are already copied and known to be constant.
+            void* glPosPtr = NULL;
+            size_t posBytes = 0;
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsMapResources(1, &s.cudaPosBuffer, stream));
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsResourceGetMappedPointer(&glPosPtr, &posBytes, s.cudaPosBuffer));
+            NVDR_CHECK(posBytes >= posCount * sizeof(float), "mapped GL position buffer size mismatch");
+            NVDR_CHECK_CUDA_ERROR(cudaMemcpyAsync(glPosPtr, posPtr, posCount * sizeof(float), cudaMemcpyDeviceToDevice, stream));
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnmapResources(1, &s.cudaPosBuffer, stream));
+        }
+    }
+
+    // Select program based on whether we have a depth peeling input or not.
+    if (peeling_idx < 1)
+    {
+        // Normal case: No peeling, or peeling disabled.
+        NVDR_CHECK_GL_ERROR(glUseProgram(s.glProgram));
+    }
+    else
+    {
+        // If we don't have a third buffer yet, create one.
+        if (!s.cudaPrevOutBuffer)
+        {
+            NVDR_CHECK_GL_ERROR(glBindTexture(GL_TEXTURE_2D_ARRAY, s.glPrevOutBuffer));
+            NVDR_CHECK_GL_ERROR(glTexImage3D(GL_TEXTURE_2D_ARRAY, 0, GL_RGBA32F, s.width, s.height, s.depth, 0, GL_RGBA, GL_UNSIGNED_BYTE, 0));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_MAG_FILTER, GL_NEAREST));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_MIN_FILTER, GL_NEAREST));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_WRAP_S, GL_CLAMP_TO_EDGE));
+            NVDR_CHECK_GL_ERROR(glTexParameteri(GL_TEXTURE_2D_ARRAY, GL_TEXTURE_WRAP_T, GL_CLAMP_TO_EDGE));
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsGLRegisterImage(&s.cudaPrevOutBuffer, s.glPrevOutBuffer, GL_TEXTURE_3D, cudaGraphicsRegisterFlagsReadOnly));
+        }
+
+        // Swap the GL buffers.
+        GLuint glTempBuffer = s.glPrevOutBuffer;
+        s.glPrevOutBuffer = s.glColorBuffer[0];
+        s.glColorBuffer[0] = glTempBuffer;
+
+        // Swap the Cuda buffers.
+        cudaGraphicsResource_t cudaTempBuffer = s.cudaPrevOutBuffer;
+        s.cudaPrevOutBuffer = s.cudaColorBuffer[0];
+        s.cudaColorBuffer[0] = cudaTempBuffer;
+
+        // Bind the new output buffer.
+        NVDR_CHECK_GL_ERROR(glBindTexture(GL_TEXTURE_2D_ARRAY, s.glColorBuffer[0]));
+        NVDR_CHECK_GL_ERROR(glFramebufferTexture(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0, s.glColorBuffer[0], 0));
+
+        // Bind old buffer as the input texture.
+        NVDR_CHECK_GL_ERROR(glBindTexture(GL_TEXTURE_2D_ARRAY, s.glPrevOutBuffer));
+
+        // Activate the correct program.
+        NVDR_CHECK_GL_ERROR(glUseProgram(s.glProgramDP));
+    }
+
+    // Set viewport, clear color buffer(s) and depth/stencil buffer.
+    NVDR_CHECK_GL_ERROR(glViewport(0, 0, width, height));
+    NVDR_CHECK_GL_ERROR(glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT | GL_STENCIL_BUFFER_BIT));
+
+    // If outputting bary differentials, set resolution uniform
+    if (s.enableDB)
+        NVDR_CHECK_GL_ERROR(glUniform2f(0, 2.f / (float)width, 2.f / (float)height));
+
+    // Set the dummy uniform if depth modification workaround is active.
+    if (s.enableZModify)
+        NVDR_CHECK_GL_ERROR(glUniform1f(1, 0.f));
+
+    // Render the meshes.
+    if (depth == 1 && !rangesPtr)
+    {
+        // Trivial case.
+        NVDR_CHECK_GL_ERROR(glDrawElements(GL_TRIANGLES, triCount, GL_UNSIGNED_INT, 0));
+    }
+    else
+    {
+        // Populate a buffer for draw commands and execute it.
+        std::vector<GLDrawCmd> drawCmdBuffer(depth);
+
+        if (!rangesPtr)
+        {
+            // Fill in range array to instantiate the same triangles for each output layer.
+            // Triangle IDs starts at zero (i.e., one) for each layer, so they correspond to
+            // the first dimension in addressing the triangle array.
+            for (int i=0; i < depth; i++)
+            {
+                GLDrawCmd& cmd = drawCmdBuffer[i];
+                cmd.firstIndex    = 0;
+                cmd.count         = triCount;
+                cmd.baseVertex    = vtxPerInstance * i;
+                cmd.baseInstance  = 0;
+                cmd.instanceCount = 1;
+            }
+        }
+        else
+        {
+            // Fill in the range array according to user-given ranges. Triangle IDs point
+            // to the input triangle array, NOT index within range, so they correspond to
+            // the first dimension in addressing the triangle array.
+            for (int i=0, j=0; i < depth; i++)
+            {
+                GLDrawCmd& cmd = drawCmdBuffer[i];
+                int first = rangesPtr[j++];
+                int count = rangesPtr[j++];
+                NVDR_CHECK(first >= 0 && count >= 0, "range contains negative values");
+                NVDR_CHECK((first + count) * 3 <= triCount, "range extends beyond end of triangle buffer");
+                cmd.firstIndex    = first * 3;
+                cmd.count         = count * 3;
+                cmd.baseVertex    = 0;
+                cmd.baseInstance  = first;
+                cmd.instanceCount = 1;
+            }
+        }
+
+        // Draw!
+        NVDR_CHECK_GL_ERROR(glMultiDrawElementsIndirect(GL_TRIANGLES, GL_UNSIGNED_INT, &drawCmdBuffer[0], depth, sizeof(GLDrawCmd)));
+    }
+}
+
+void rasterizeCopyResults(NVDR_CTX_ARGS, RasterizeGLState& s, cudaStream_t stream, float** outputPtr, int width, int height, int depth)
+{
+    // Copy color buffers to output tensors.
+    cudaArray_t array = 0;
+    cudaChannelFormatDesc arrayDesc = {};   // For error checking.
+    cudaExtent arrayExt = {};               // For error checking.
+    int num_outputs = s.enableDB ? 2 : 1;
+    NVDR_CHECK_CUDA_ERROR(cudaGraphicsMapResources(num_outputs, s.cudaColorBuffer, stream));
+    for (int i=0; i < num_outputs; i++)
+    {
+        NVDR_CHECK_CUDA_ERROR(cudaGraphicsSubResourceGetMappedArray(&array, s.cudaColorBuffer[i], 0, 0));
+        NVDR_CHECK_CUDA_ERROR(cudaArrayGetInfo(&arrayDesc, &arrayExt, NULL, array));
+        NVDR_CHECK(arrayDesc.f == cudaChannelFormatKindFloat, "CUDA mapped array data kind mismatch");
+        NVDR_CHECK(arrayDesc.x == 32 && arrayDesc.y == 32 && arrayDesc.z == 32 && arrayDesc.w == 32, "CUDA mapped array data width mismatch");
+        NVDR_CHECK(arrayExt.width >= width && arrayExt.height >= height && arrayExt.depth >= depth, "CUDA mapped array extent mismatch");
+        cudaMemcpy3DParms p = {0};
+        p.srcArray = array;
+        p.dstPtr.ptr = outputPtr[i];
+        p.dstPtr.pitch = width * 4 * sizeof(float);
+        p.dstPtr.xsize = width;
+        p.dstPtr.ysize = height;
+        p.extent.width = width;
+        p.extent.height = height;
+        p.extent.depth = depth;
+        p.kind = cudaMemcpyDeviceToDevice;
+        NVDR_CHECK_CUDA_ERROR(cudaMemcpy3DAsync(&p, stream));
+    }
+    NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnmapResources(num_outputs, s.cudaColorBuffer, stream));
+}
+
+void rasterizeReleaseBuffers(NVDR_CTX_ARGS, RasterizeGLState& s)
+{
+    int num_outputs = s.enableDB ? 2 : 1;
+
+    if (s.cudaPosBuffer)
+    {
+        NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaPosBuffer));
+        s.cudaPosBuffer = 0;
+    }
+
+    if (s.cudaTriBuffer)
+    {
+        NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaTriBuffer));
+        s.cudaTriBuffer = 0;
+    }
+
+    for (int i=0; i < num_outputs; i++)
+    {
+        if (s.cudaColorBuffer[i])
+        {
+            NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaColorBuffer[i]));
+            s.cudaColorBuffer[i] = 0;
+        }
+    }
+
+    if (s.cudaPrevOutBuffer)
+    {
+        NVDR_CHECK_CUDA_ERROR(cudaGraphicsUnregisterResource(s.cudaPrevOutBuffer));
+        s.cudaPrevOutBuffer = 0;
+    }
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/rasterize_gl.h b/extensions/nvdiffrast/nvdiffrast/common/rasterize_gl.h
new file mode 100644
index 0000000000000000000000000000000000000000..27537c5624286af9c2cba9dc908f400abc9ddfdf
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/rasterize_gl.h
@@ -0,0 +1,60 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+
+//------------------------------------------------------------------------
+// Do not try to include OpenGL stuff when compiling CUDA kernels for torch.
+
+#if !(defined(NVDR_TORCH) && defined(__CUDACC__))
+#include "framework.h"
+#include "glutil.h"
+
+//------------------------------------------------------------------------
+// OpenGL-related persistent state for forward op.
+
+struct RasterizeGLState // Must be initializable by memset to zero.
+{
+    int                     width;              // Allocated frame buffer width.
+    int                     height;             // Allocated frame buffer height.
+    int                     depth;              // Allocated frame buffer depth.
+    int                     posCount;           // Allocated position buffer in floats.
+    int                     triCount;           // Allocated triangle buffer in ints.
+    GLContext               glctx;
+    GLuint                  glFBO;
+    GLuint                  glColorBuffer[2];
+    GLuint                  glPrevOutBuffer;
+    GLuint                  glDepthStencilBuffer;
+    GLuint                  glVAO;
+    GLuint                  glTriBuffer;
+    GLuint                  glPosBuffer;
+    GLuint                  glProgram;
+    GLuint                  glProgramDP;
+    GLuint                  glVertexShader;
+    GLuint                  glGeometryShader;
+    GLuint                  glFragmentShader;
+    GLuint                  glFragmentShaderDP;
+    cudaGraphicsResource_t  cudaColorBuffer[2];
+    cudaGraphicsResource_t  cudaPrevOutBuffer;
+    cudaGraphicsResource_t  cudaPosBuffer;
+    cudaGraphicsResource_t  cudaTriBuffer;
+    int                     enableDB;
+    int                     enableZModify;      // Modify depth in shader, workaround for a rasterization issue on A100.
+};
+
+//------------------------------------------------------------------------
+// Shared C++ code prototypes.
+
+void rasterizeInitGLContext(NVDR_CTX_ARGS, RasterizeGLState& s, int cudaDeviceIdx);
+void rasterizeResizeBuffers(NVDR_CTX_ARGS, RasterizeGLState& s, bool& changes, int posCount, int triCount, int width, int height, int depth);
+void rasterizeRender(NVDR_CTX_ARGS, RasterizeGLState& s, cudaStream_t stream, const float* posPtr, int posCount, int vtxPerInstance, const int32_t* triPtr, int triCount, const int32_t* rangesPtr, int width, int height, int depth, int peeling_idx);
+void rasterizeCopyResults(NVDR_CTX_ARGS, RasterizeGLState& s, cudaStream_t stream, float** outputPtr, int width, int height, int depth);
+void rasterizeReleaseBuffers(NVDR_CTX_ARGS, RasterizeGLState& s);
+
+//------------------------------------------------------------------------
+#endif // !(defined(NVDR_TORCH) && defined(__CUDACC__))
diff --git a/extensions/nvdiffrast/nvdiffrast/common/texture.cpp b/extensions/nvdiffrast/nvdiffrast/common/texture.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..51633e10120b4dc465e5283241a38c95db31f8dc
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/texture.cpp
@@ -0,0 +1,104 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "framework.h"
+#include "texture.h"
+
+//------------------------------------------------------------------------
+// Mip stack construction and access helpers.
+
+void raiseMipSizeError(NVDR_CTX_ARGS, const TextureKernelParams& p)
+{
+    char buf[1024];
+    int bufsz = 1024;
+
+    std::string msg = "Mip-map size error - cannot downsample an odd extent greater than 1. Resize the texture so that both spatial extents are powers of two, or limit the number of mip maps using max_mip_level argument.\n";
+
+    int w = p.texWidth;
+    int h = p.texHeight;
+    bool ew = false;
+    bool eh = false;
+
+    msg += "Attempted mip stack construction:\n";
+    msg +=               "level  width height\n";
+    msg +=               "-----  ----- ------\n";
+    snprintf(buf, bufsz, "base   %5d  %5d\n", w, h);
+    msg += buf;
+
+    int mipTotal = 0;
+    int level = 0;
+    while ((w|h) > 1 && !(ew || eh)) // Stop at first impossible size.
+    {
+        // Current level.
+        level += 1;
+
+        // Determine if downsampling fails.
+        ew = ew || (w > 1 && (w & 1));
+        eh = eh || (h > 1 && (h & 1));
+
+        // Downsample.
+        if (w > 1) w >>= 1;
+        if (h > 1) h >>= 1;
+
+        // Append level size to error message.
+        snprintf(buf, bufsz, "mip %-2d ", level);
+        msg += buf; 
+        if (ew) snprintf(buf, bufsz, "  err  ");
+        else    snprintf(buf, bufsz, "%5d  ", w);
+        msg += buf;
+        if (eh) snprintf(buf, bufsz, "  err\n");
+        else    snprintf(buf, bufsz, "%5d\n", h);
+        msg += buf;
+    }
+
+    NVDR_CHECK(0, msg);
+}
+
+int calculateMipInfo(NVDR_CTX_ARGS, TextureKernelParams& p, int* mipOffsets)
+{
+    // No levels at all?
+    if (p.mipLevelLimit == 0)
+    {
+        p.mipLevelMax = 0;
+        return 0;
+    }
+
+    // Current level size.
+    int w = p.texWidth;
+    int h = p.texHeight;
+
+    int mipTotal = 0;
+    int level = 0;
+    int c = (p.boundaryMode == TEX_BOUNDARY_MODE_CUBE) ? (p.channels * 6) : p.channels;
+    mipOffsets[0] = 0;
+    while ((w|h) > 1)
+    {
+        // Current level.
+        level += 1;
+
+        // Quit if cannot downsample.
+        if ((w > 1 && (w & 1)) || (h > 1 && (h & 1)))
+            raiseMipSizeError(NVDR_CTX_PARAMS, p);
+
+        // Downsample.
+        if (w > 1) w >>= 1;
+        if (h > 1) h >>= 1;
+
+        mipOffsets[level] = mipTotal; // Store the mip offset (#floats).
+        mipTotal += w * h * p.texDepth * c;
+
+        // Hit the level limit?
+        if (p.mipLevelLimit >= 0 && level == p.mipLevelLimit)
+            break;
+    }
+
+    p.mipLevelMax = level;
+    return mipTotal;
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/texture.h b/extensions/nvdiffrast/nvdiffrast/common/texture.h
new file mode 100644
index 0000000000000000000000000000000000000000..f79b600fff0256cdadd38e265b49366549434ef8
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/texture.h
@@ -0,0 +1,78 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include "framework.h"
+
+//------------------------------------------------------------------------
+// Constants.
+
+#define TEX_DEBUG_MIP_RETAIN_VARIANCE           0   // For debugging
+#define TEX_FWD_MAX_KERNEL_BLOCK_WIDTH          8
+#define TEX_FWD_MAX_KERNEL_BLOCK_HEIGHT         8
+#define TEX_FWD_MAX_MIP_KERNEL_BLOCK_WIDTH      8
+#define TEX_FWD_MAX_MIP_KERNEL_BLOCK_HEIGHT     8
+#define TEX_GRAD_MAX_KERNEL_BLOCK_WIDTH         8
+#define TEX_GRAD_MAX_KERNEL_BLOCK_HEIGHT        8
+#define TEX_GRAD_MAX_MIP_KERNEL_BLOCK_WIDTH     8
+#define TEX_GRAD_MAX_MIP_KERNEL_BLOCK_HEIGHT    8
+#define TEX_MAX_MIP_LEVEL                       16  // Currently a texture cannot be larger than 2 GB because we use 32-bit indices everywhere.
+#define TEX_MODE_NEAREST                        0   // Nearest on base level.
+#define TEX_MODE_LINEAR                         1   // Bilinear on base level.
+#define TEX_MODE_LINEAR_MIPMAP_NEAREST          2   // Bilinear on nearest mip level.
+#define TEX_MODE_LINEAR_MIPMAP_LINEAR           3   // Trilinear.
+#define TEX_MODE_COUNT                          4
+#define TEX_BOUNDARY_MODE_CUBE                  0   // Cube map mode.
+#define TEX_BOUNDARY_MODE_WRAP                  1   // Wrap (u, v).
+#define TEX_BOUNDARY_MODE_CLAMP                 2   // Clamp (u, v).
+#define TEX_BOUNDARY_MODE_ZERO                  3   // Pad with zeros.
+#define TEX_BOUNDARY_MODE_COUNT                 4
+
+//------------------------------------------------------------------------
+// CUDA kernel params.
+
+struct TextureKernelParams
+{
+    const float*    tex[TEX_MAX_MIP_LEVEL];         // Incoming texture buffer with mip levels.
+    const float*    uv;                             // Incoming texcoord buffer.
+    const float*    uvDA;                           // Incoming uv pixel diffs or NULL.
+    const float*    mipLevelBias;                   // Incoming mip level bias or NULL.
+    const float*    dy;                             // Incoming output gradient.
+    float*          out;                            // Outgoing texture data.
+    float*          gradTex[TEX_MAX_MIP_LEVEL];     // Outgoing texture gradients with mip levels.
+    float*          gradUV;                         // Outgoing texcoord gradient.
+    float*          gradUVDA;                       // Outgoing texcoord pixel differential gradient.
+    float*          gradMipLevelBias;               // Outgoing mip level bias gradient.
+    int             enableMip;                      // If true, we have uv_da and/or mip_level_bias input(s), and a mip tensor.
+    int             filterMode;                     // One of the TEX_MODE_ constants.
+    int             boundaryMode;                   // One of the TEX_BOUNDARY_MODE_ contants.
+    int             texConst;                       // If true, texture is known to be constant.
+    int             mipLevelLimit;                  // Mip level limit coming from the op.
+    int             channels;                       // Number of texture channels.
+    int             imgWidth;                       // Image width.
+    int             imgHeight;                      // Image height.
+    int             texWidth;                       // Texture width.
+    int             texHeight;                      // Texture height.
+    int             texDepth;                       // Texture depth.
+    int             n;                              // Minibatch size.
+    int             mipLevelMax;                    // Maximum mip level index. Zero if mips disabled.
+    int             mipLevelOut;                    // Mip level being calculated in builder kernel.
+};
+
+//------------------------------------------------------------------------
+// C++ helper function prototypes.
+
+void raiseMipSizeError(NVDR_CTX_ARGS, const TextureKernelParams& p);
+int calculateMipInfo(NVDR_CTX_ARGS, TextureKernelParams& p, int* mipOffsets);
+
+//------------------------------------------------------------------------
+// Macros.
+
+#define mipLevelSize(p, i) make_int2(((p).texWidth >> (i)) > 1 ? ((p).texWidth >> (i)) : 1, ((p).texHeight >> (i)) > 1 ? ((p).texHeight >> (i)) : 1)
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/common/texture_.cu b/extensions/nvdiffrast/nvdiffrast/common/texture_.cu
new file mode 100644
index 0000000000000000000000000000000000000000..490b8d68dd62398e05086843f138bd7f3510f449
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/common/texture_.cu
@@ -0,0 +1,1156 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "common.h"
+#include "texture.h"
+
+//------------------------------------------------------------------------
+// Memory access and math helpers.
+
+static __device__ __forceinline__ void accum_from_mem(float* a, int s, float  b, float c) { a[0] += b * c; }
+static __device__ __forceinline__ void accum_from_mem(float* a, int s, float2 b, float c) { a[0] += b.x * c; a[s] += b.y * c; }
+static __device__ __forceinline__ void accum_from_mem(float* a, int s, float4 b, float c) { a[0] += b.x * c; a[s] += b.y * c; a[2*s] += b.z * c; a[3*s] += b.w * c; }
+static __device__ __forceinline__ void accum_to_mem(float&  a, float* b, int s) { a += b[0]; }
+static __device__ __forceinline__ void accum_to_mem(float2& a, float* b, int s) { float2 v = a; v.x += b[0]; v.y += b[s]; a = v; }
+static __device__ __forceinline__ void accum_to_mem(float4& a, float* b, int s) { float4 v = a; v.x += b[0]; v.y += b[s]; v.z += b[2*s]; v.w += b[3*s]; a = v; }
+static __device__ __forceinline__ bool isfinite_vec3(const float3& a) { return isfinite(a.x) && isfinite(a.y) && isfinite(a.z); }
+static __device__ __forceinline__ bool isfinite_vec4(const float4& a) { return isfinite(a.x) && isfinite(a.y) && isfinite(a.z) && isfinite(a.w); }
+template<class T> static __device__ __forceinline__ T lerp  (const T& a, const T& b, float c) { return a + c * (b - a); }
+template<class T> static __device__ __forceinline__ T bilerp(const T& a, const T& b, const T& c, const T& d, const float2& e) { return lerp(lerp(a, b, e.x), lerp(c, d, e.x), e.y); }
+
+//------------------------------------------------------------------------
+// Cube map wrapping for smooth filtering across edges and corners. At corners,
+// one of the texture coordinates will be negative. For correct interpolation,
+// the missing texel must take the average color of the other three.
+
+static __constant__ uint32_t c_cubeWrapMask1[48] =
+{
+    0x1530a440, 0x1133a550, 0x6103a110, 0x1515aa44, 0x6161aa11, 0x40154a04, 0x44115a05, 0x04611a01,
+    0x2630a440, 0x2233a550, 0x5203a110, 0x2626aa44, 0x5252aa11, 0x40264a04, 0x44225a05, 0x04521a01,
+    0x32608064, 0x3366a055, 0x13062091, 0x32328866, 0x13132299, 0x50320846, 0x55330a55, 0x05130219,
+    0x42508064, 0x4455a055, 0x14052091, 0x42428866, 0x14142299, 0x60420846, 0x66440a55, 0x06140219,
+    0x5230a044, 0x5533a055, 0x1503a011, 0x5252aa44, 0x1515aa11, 0x40520a44, 0x44550a55, 0x04150a11,
+    0x6130a044, 0x6633a055, 0x2603a011, 0x6161aa44, 0x2626aa11, 0x40610a44, 0x44660a55, 0x04260a11,
+};
+
+static __constant__ uint8_t c_cubeWrapMask2[48] =
+{
+    0x26, 0x33, 0x11, 0x05, 0x00, 0x09, 0x0c, 0x04, 0x04, 0x00, 0x00, 0x05, 0x00, 0x81, 0xc0, 0x40,
+    0x02, 0x03, 0x09, 0x00, 0x0a, 0x00, 0x00, 0x02, 0x64, 0x30, 0x90, 0x55, 0xa0, 0x99, 0xcc, 0x64,
+    0x24, 0x30, 0x10, 0x05, 0x00, 0x01, 0x00, 0x00, 0x06, 0x03, 0x01, 0x05, 0x00, 0x89, 0xcc, 0x44,
+};
+
+static __device__ __forceinline__ int4 wrapCubeMap(int face, int ix0, int ix1, int iy0, int iy1, int w)
+{
+    // Calculate case number.
+    int cx = (ix0 < 0) ? 0 : (ix1 >= w) ? 2 : 1;
+    int cy = (iy0 < 0) ? 0 : (iy1 >= w) ? 6 : 3;
+    int c = cx + cy;
+    if (c >= 5)
+        c--;
+    c = (face << 3) + c;
+
+    // Compute coordinates and faces.
+    unsigned int m = c_cubeWrapMask1[c];
+    int x0 = (m >>  0) & 3; x0 = (x0 == 0) ? 0 : (x0 == 1) ? ix0 : iy0;
+    int x1 = (m >>  2) & 3; x1 = (x1 == 0) ? 0 : (x1 == 1) ? ix1 : iy0;
+    int x2 = (m >>  4) & 3; x2 = (x2 == 0) ? 0 : (x2 == 1) ? ix0 : iy1;
+    int x3 = (m >>  6) & 3; x3 = (x3 == 0) ? 0 : (x3 == 1) ? ix1 : iy1;
+    int y0 = (m >>  8) & 3; y0 = (y0 == 0) ? 0 : (y0 == 1) ? ix0 : iy0;
+    int y1 = (m >> 10) & 3; y1 = (y1 == 0) ? 0 : (y1 == 1) ? ix1 : iy0;
+    int y2 = (m >> 12) & 3; y2 = (y2 == 0) ? 0 : (y2 == 1) ? ix0 : iy1;
+    int y3 = (m >> 14) & 3; y3 = (y3 == 0) ? 0 : (y3 == 1) ? ix1 : iy1;
+    int f0 = ((m >> 16) & 15) - 1;
+    int f1 = ((m >> 20) & 15) - 1;
+    int f2 = ((m >> 24) & 15) - 1;
+    int f3 = ((m >> 28)     ) - 1;
+
+    // Flips.
+    unsigned int f = c_cubeWrapMask2[c];
+    int w1 = w - 1;
+    if (f & 0x01) x0 = w1 - x0;
+    if (f & 0x02) x1 = w1 - x1;
+    if (f & 0x04) x2 = w1 - x2;
+    if (f & 0x08) x3 = w1 - x3;
+    if (f & 0x10) y0 = w1 - y0;
+    if (f & 0x20) y1 = w1 - y1;
+    if (f & 0x40) y2 = w1 - y2;
+    if (f & 0x80) y3 = w1 - y3;
+
+    // Done.
+    int4 tcOut;
+    tcOut.x = x0 + (y0 + f0 * w) * w;
+    tcOut.y = x1 + (y1 + f1 * w) * w;
+    tcOut.z = x2 + (y2 + f2 * w) * w;
+    tcOut.w = x3 + (y3 + f3 * w) * w;
+    return tcOut;
+}
+
+//------------------------------------------------------------------------
+// Cube map indexing and gradient functions.
+
+// Map a 3D lookup vector into an (s,t) face coordinates (returned in first .
+// two parameters) and face index.
+static __device__ __forceinline__ int indexCubeMap(float& x, float& y, float z)
+{
+    float ax = fabsf(x);
+    float ay = fabsf(y);
+    float az = fabsf(z);
+    int idx;
+    float c;
+    if (az > fmaxf(ax, ay)) { idx = 4; c = z; }
+    else if (ay > ax)       { idx = 2; c = y; y = z; }
+    else                    { idx = 0; c = x; x = z; }
+    if (c < 0.f) idx += 1;
+    float m = __frcp_rz(fabsf(c)) * .5;
+    float m0 = __uint_as_float(__float_as_uint(m) ^ ((0x21u >> idx) << 31));
+    float m1 = (idx != 2) ? -m : m;
+    x = x * m0 + .5;
+    y = y * m1 + .5;
+    if (!isfinite(x) || !isfinite(y))
+        return -1; // Invalid uv.
+    x = fminf(fmaxf(x, 0.f), 1.f);
+    y = fminf(fmaxf(y, 0.f), 1.f);
+    return idx;
+}
+
+// Based on dA/d{s,t}, compute dA/d{x,y,z} at a given 3D lookup vector.
+static __device__ __forceinline__ float3 indexCubeMapGrad(float3 uv, float gu, float gv)
+{
+    float ax = fabsf(uv.x);
+    float ay = fabsf(uv.y);
+    float az = fabsf(uv.z);
+    int idx;
+    float c;
+    float c0 = gu;
+    float c1 = gv;
+    if (az > fmaxf(ax, ay)) { idx = 0x10; c = uv.z; c0 *= uv.x; c1 *= uv.y; }
+    else if (ay > ax)       { idx = 0x04; c = uv.y; c0 *= uv.x; c1 *= uv.z; }
+    else                    { idx = 0x01; c = uv.x; c0 *= uv.z; c1 *= uv.y; }
+    if (c < 0.f) idx += idx;
+    float m = __frcp_rz(fabsf(c));
+    c0 = (idx & 0x34) ? -c0 : c0;
+    c1 = (idx & 0x2e) ? -c1 : c1;
+    float gl = (c0 + c1) * m;
+    float gx = (idx & 0x03) ? gl : (idx & 0x20) ? -gu : gu;
+    float gy = (idx & 0x0c) ? gl : -gv;
+    float gz = (idx & 0x30) ? gl : (idx & 0x03) ? gu : gv;
+    gz = (idx & 0x09) ? -gz : gz;
+    float3 res = make_float3(gx, gy, gz) * (m * .5f);
+    if (!isfinite_vec3(res))
+        return make_float3(0.f, 0.f, 0.f); // Invalid uv.
+    return res;
+}
+
+// Based on dL/d(d{s,t}/s{X,Y}), compute dL/d(d{x,y,z}/d{X,Y}). This is just two
+// indexCubeMapGrad() functions rolled together.
+static __device__ __forceinline__ void indexCubeMapGrad4(float3 uv, float4 dw, float3& g0, float3& g1)
+{
+    float ax = fabsf(uv.x);
+    float ay = fabsf(uv.y);
+    float az = fabsf(uv.z);
+    int idx;
+    float c, c0, c1;
+    if (az > fmaxf(ax, ay)) { idx = 0x10; c = uv.z; c0 = uv.x; c1 = uv.y; }
+    else if (ay > ax)       { idx = 0x04; c = uv.y; c0 = uv.x; c1 = uv.z; }
+    else                    { idx = 0x01; c = uv.x; c0 = uv.z; c1 = uv.y; }
+    if (c < 0.f) idx += idx;
+    float m = __frcp_rz(fabsf(c));
+    c0 = (idx & 0x34) ? -c0 : c0;
+    c1 = (idx & 0x2e) ? -c1 : c1;
+    float gl0 = (dw.x * c0 + dw.z * c1) * m;
+    float gl1 = (dw.y * c0 + dw.w * c1) * m;
+    float gx0 = (idx & 0x03) ? gl0 : (idx & 0x20) ? -dw.x : dw.x;
+    float gx1 = (idx & 0x03) ? gl1 : (idx & 0x20) ? -dw.y : dw.y;
+    float gy0 = (idx & 0x0c) ? gl0 : -dw.z;
+    float gy1 = (idx & 0x0c) ? gl1 : -dw.w;
+    float gz0 = (idx & 0x30) ? gl0 : (idx & 0x03) ? dw.x : dw.z;
+    float gz1 = (idx & 0x30) ? gl1 : (idx & 0x03) ? dw.y : dw.w;
+    if (idx & 0x09)
+    {
+        gz0 = -gz0;
+        gz1 = -gz1;
+    }
+    g0 = make_float3(gx0, gy0, gz0) * (m * .5f);
+    g1 = make_float3(gx1, gy1, gz1) * (m * .5f);
+    if (!isfinite_vec3(g0) || !isfinite_vec3(g1))
+    {
+        g0 = make_float3(0.f, 0.f, 0.f); // Invalid uv.
+        g1 = make_float3(0.f, 0.f, 0.f);
+    }
+}
+
+// Compute d{s,t}/d{X,Y} based on d{x,y,z}/d{X,Y} at a given 3D lookup vector.
+// Result is (ds/dX, ds/dY, dt/dX, dt/dY).
+static __device__ __forceinline__ float4 indexCubeMapGradST(float3 uv, float3 dvdX, float3 dvdY)
+{
+    float ax = fabsf(uv.x);
+    float ay = fabsf(uv.y);
+    float az = fabsf(uv.z);
+    int idx;
+    float c, gu, gv;
+    if (az > fmaxf(ax, ay)) { idx = 0x10; c = uv.z; gu = uv.x; gv = uv.y; }
+    else if (ay > ax)       { idx = 0x04; c = uv.y; gu = uv.x; gv = uv.z; }
+    else                    { idx = 0x01; c = uv.x; gu = uv.z; gv = uv.y; }
+    if (c < 0.f) idx += idx;
+    if (idx & 0x09)
+    {
+        dvdX.z = -dvdX.z;
+        dvdY.z = -dvdY.z;
+    }
+    float m = __frcp_rz(fabsf(c));
+    float dm = m * .5f;
+    float mm = m * dm;
+    gu *= (idx & 0x34) ? -mm : mm;
+    gv *= (idx & 0x2e) ? -mm : mm;
+
+    float4 res;
+    if (idx & 0x03)
+    {
+        res = make_float4(gu * dvdX.x + dm * dvdX.z,
+                          gu * dvdY.x + dm * dvdY.z,
+                          gv * dvdX.x - dm * dvdX.y,
+                          gv * dvdY.x - dm * dvdY.y);
+    }
+    else if (idx & 0x0c)
+    {
+        res = make_float4(gu * dvdX.y + dm * dvdX.x,
+                          gu * dvdY.y + dm * dvdY.x,
+                          gv * dvdX.y + dm * dvdX.z,
+                          gv * dvdY.y + dm * dvdY.z);
+    }
+    else // (idx & 0x30)
+    {
+        res = make_float4(gu * dvdX.z + copysignf(dm, c) * dvdX.x,
+                          gu * dvdY.z + copysignf(dm, c) * dvdY.x,
+                          gv * dvdX.z - dm * dvdX.y,
+                          gv * dvdY.z - dm * dvdY.y);
+    }
+
+    if (!isfinite_vec4(res))
+        return make_float4(0.f, 0.f, 0.f, 0.f);
+
+    return res;
+}
+
+// Compute d(d{s,t}/d{X,Y})/d{x,y,z}, i.e., how the pixel derivatives of 2D face
+// coordinates change w.r.t. 3D texture coordinate vector, returned as follows:
+//   |  d(ds/dX)/dx  d(ds/dY)/dx  d(dt/dX)/dx  d(dt/dY)/dx  |
+//   |  d(ds/dX)/dy  d(ds/dY)/dy  d(dt/dX)/dy  d(dt/dY)/dy  |
+//   |  d(ds/dX)/dz  d(ds/dY)/dz  d(dt/dX)/dz  d(dt/dY)/dz  |
+static __device__ __forceinline__ void indexCubeMapGrad2(float3 uv, float3 dvdX, float3 dvdY, float4& dx, float4& dy, float4& dz)
+{
+    float ax = fabsf(uv.x);
+    float ay = fabsf(uv.y);
+    float az = fabsf(uv.z);
+    int idx;
+    float c, gu, gv;
+    if (az > fmaxf(ax, ay)) { idx = 0x10; c = uv.z; gu = uv.x; gv = uv.y; }
+    else if (ay > ax)       { idx = 0x04; c = uv.y; gu = uv.x; gv = uv.z; }
+    else                    { idx = 0x01; c = uv.x; gu = uv.z; gv = uv.y; }
+    if (c < 0.f) idx += idx;
+
+    if (idx & 0x09)
+    {
+        dvdX.z = -dvdX.z;
+        dvdY.z = -dvdY.z;
+    }
+
+    float m = __frcp_rz(c);
+    float dm = -m * fabsf(m) * .5;
+    float mm = m * m * .5;
+    float mu = (idx & 0x34) ? -mm : mm;
+    float mv = (idx & 0x2e) ? -mm : mm;
+    gu *= -2.0 * m * mu;
+    gv *= -2.0 * m * mv;
+
+    if (idx & 0x03)
+    {
+        dx.x = gu * dvdX.x + dm * dvdX.z;
+        dx.y = gu * dvdY.x + dm * dvdY.z;
+        dx.z = gv * dvdX.x - dm * dvdX.y;
+        dx.w = gv * dvdY.x - dm * dvdY.y;
+        dy.x = 0.f;
+        dy.y = 0.f;
+        dy.z = mv * dvdX.x;
+        dy.w = mv * dvdY.x;
+        dz.x = mu * dvdX.x;
+        dz.y = mu * dvdY.x;
+        dz.z = 0.f;
+        dz.w = 0.f;
+    }
+    else if (idx & 0x0c)
+    {
+        dx.x = mu * dvdX.y;
+        dx.y = mu * dvdY.y;
+        dx.z = 0.f;
+        dx.w = 0.f;
+        dy.x = gu * dvdX.y + dm * dvdX.x;
+        dy.y = gu * dvdY.y + dm * dvdY.x;
+        dy.z = gv * dvdX.y + dm * dvdX.z;
+        dy.w = gv * dvdY.y + dm * dvdY.z;
+        dz.x = 0.f;
+        dz.y = 0.f;
+        dz.z = mv * dvdX.y;
+        dz.w = mv * dvdY.y;
+    }
+    else // (idx & 0x30)
+    {
+        dx.x = mu * dvdX.z;
+        dx.y = mu * dvdY.z;
+        dx.z = 0.f;
+        dx.w = 0.f;
+        dy.x = 0.f;
+        dy.y = 0.f;
+        dy.z = mv * dvdX.z;
+        dy.w = mv * dvdY.z;
+        dz.x = gu * dvdX.z - fabsf(dm) * dvdX.x;
+        dz.y = gu * dvdY.z - fabsf(dm) * dvdY.x;
+        dz.z = gv * dvdX.z - dm * dvdX.y;
+        dz.w = gv * dvdY.z - dm * dvdY.y;
+    }
+}
+
+//------------------------------------------------------------------------
+// General texture indexing.
+
+template <bool CUBE_MODE>
+static __device__ __forceinline__ int indexTextureNearest(const TextureKernelParams& p, float3 uv, int tz)
+{
+    int w = p.texWidth;
+    int h = p.texHeight;
+    float u = uv.x;
+    float v = uv.y;
+
+    // Cube map indexing.
+    if (CUBE_MODE)
+    {
+        // No wrap. Fold face index into tz right away.
+        int idx = indexCubeMap(u, v, uv.z); // Rewrites u, v.
+        if (idx < 0)
+            return -1; // Invalid uv.
+        tz = 6 * tz + idx;
+    }
+    else
+    {
+        // Handle boundary.
+        if (p.boundaryMode == TEX_BOUNDARY_MODE_WRAP)
+        {
+            u = u - (float)__float2int_rd(u);
+            v = v - (float)__float2int_rd(v);
+        }
+    }
+
+    u = u * (float)w;
+    v = v * (float)h;
+
+    int iu = __float2int_rd(u);
+    int iv = __float2int_rd(v);
+
+    // In zero boundary mode, return texture address -1.
+    if (!CUBE_MODE && p.boundaryMode == TEX_BOUNDARY_MODE_ZERO)
+    {
+        if (iu < 0 || iu >= w || iv < 0 || iv >= h)
+            return -1;
+    }
+
+    // Otherwise clamp and calculate the coordinate properly.
+    iu = min(max(iu, 0), w-1);
+    iv = min(max(iv, 0), h-1);
+    return iu + w * (iv + tz * h);
+}
+
+template <bool CUBE_MODE>
+static __device__ __forceinline__ float2 indexTextureLinear(const TextureKernelParams& p, float3 uv, int tz, int4& tcOut, int level)
+{
+    // Mip level size.
+    int2 sz = mipLevelSize(p, level);
+    int w = sz.x;
+    int h = sz.y;
+
+    // Compute texture-space u, v.
+    float u = uv.x;
+    float v = uv.y;
+    bool clampU = false;
+    bool clampV = false;
+
+    // Cube map indexing.
+    int face = 0;
+    if (CUBE_MODE)
+    {
+        // Neither clamp or wrap.
+        face = indexCubeMap(u, v, uv.z); // Rewrites u, v.
+        if (face < 0)
+        {
+            tcOut.x = tcOut.y = tcOut.z = tcOut.w = -1; // Invalid uv.
+            return make_float2(0.f, 0.f);
+        }
+        u = u * (float)w - 0.5f;
+        v = v * (float)h - 0.5f;
+    }
+    else
+    {
+        if (p.boundaryMode == TEX_BOUNDARY_MODE_WRAP)
+        {
+            // Wrap.
+            u = u - (float)__float2int_rd(u);
+            v = v - (float)__float2int_rd(v);
+        }
+
+        // Move to texel space.
+        u = u * (float)w - 0.5f;
+        v = v * (float)h - 0.5f;
+
+        if (p.boundaryMode == TEX_BOUNDARY_MODE_CLAMP)
+        {
+            // Clamp to center of edge texels.
+            u = fminf(fmaxf(u, 0.f), w - 1.f);
+            v = fminf(fmaxf(v, 0.f), h - 1.f);
+            clampU = (u == 0.f || u == w - 1.f);
+            clampV = (v == 0.f || v == h - 1.f);
+        }
+    }
+
+    // Compute texel coordinates and weights.
+    int iu0 = __float2int_rd(u);
+    int iv0 = __float2int_rd(v);
+    int iu1 = iu0 + (clampU ? 0 : 1); // Ensure zero u/v gradients with clamped.
+    int iv1 = iv0 + (clampV ? 0 : 1);
+    u -= (float)iu0;
+    v -= (float)iv0;
+
+    // Cube map wrapping.
+    bool cubeWrap = CUBE_MODE && (iu0 < 0 || iv0 < 0 || iu1 >= w || iv1 >= h);
+    if (cubeWrap)
+    {
+        tcOut = wrapCubeMap(face, iu0, iu1, iv0, iv1, w);
+        tcOut += 6 * tz * w * h;  // Bring in tz.
+        return make_float2(u, v); // Done.
+    }
+
+    // Fold cube map face into tz.
+    if (CUBE_MODE)
+        tz = 6 * tz + face;
+
+    // Wrap overflowing texel indices.
+    if (!CUBE_MODE && p.boundaryMode == TEX_BOUNDARY_MODE_WRAP)
+    {
+        if (iu0 < 0) iu0 += w;
+        if (iv0 < 0) iv0 += h;
+        if (iu1 >= w) iu1 -= w;
+        if (iv1 >= h) iv1 -= h;
+    }
+
+    // Coordinates with tz folded in.
+    int iu0z = iu0 + tz * w * h;
+    int iu1z = iu1 + tz * w * h;
+    tcOut.x = iu0z + w * iv0;
+    tcOut.y = iu1z + w * iv0;
+    tcOut.z = iu0z + w * iv1;
+    tcOut.w = iu1z + w * iv1;
+
+    // Invalidate texture addresses outside unit square if we are in zero mode.
+    if (!CUBE_MODE && p.boundaryMode == TEX_BOUNDARY_MODE_ZERO)
+    {
+        bool iu0_out = (iu0 < 0 || iu0 >= w);
+        bool iu1_out = (iu1 < 0 || iu1 >= w);
+        bool iv0_out = (iv0 < 0 || iv0 >= h);
+        bool iv1_out = (iv1 < 0 || iv1 >= h);
+        if (iu0_out || iv0_out) tcOut.x = -1;
+        if (iu1_out || iv0_out) tcOut.y = -1;
+        if (iu0_out || iv1_out) tcOut.z = -1;
+        if (iu1_out || iv1_out) tcOut.w = -1;
+    }
+
+    // All done.
+    return make_float2(u, v);
+}
+
+//------------------------------------------------------------------------
+// Mip level calculation.
+
+template <bool CUBE_MODE, bool BIAS_ONLY, int FILTER_MODE>
+static __device__ __forceinline__ void calculateMipLevel(int& level0, int& level1, float& flevel, const TextureKernelParams& p, int pidx, float3 uv, float4* pdw, float3* pdfdv)
+{
+    // Do nothing if mips not in use.
+    if (FILTER_MODE == TEX_MODE_NEAREST || FILTER_MODE == TEX_MODE_LINEAR)
+        return;
+
+    // Determine mip level based on UV pixel derivatives. If no derivatives are given (mip level bias only), leave as zero.
+    if (!BIAS_ONLY)
+    {
+        // Get pixel derivatives of texture coordinates.
+        float4 uvDA;
+        float3 dvdX, dvdY; // Gradients use these later.
+        if (CUBE_MODE)
+        {
+            // Fetch.
+            float2 d0 = ((const float2*)p.uvDA)[3 * pidx + 0];
+            float2 d1 = ((const float2*)p.uvDA)[3 * pidx + 1];
+            float2 d2 = ((const float2*)p.uvDA)[3 * pidx + 2];
+
+            // Map d{x,y,z}/d{X,Y} into d{s,t}/d{X,Y}.
+            dvdX = make_float3(d0.x, d1.x, d2.x); // d{x,y,z}/dX
+            dvdY = make_float3(d0.y, d1.y, d2.y); // d{x,y,z}/dY
+            uvDA = indexCubeMapGradST(uv, dvdX, dvdY); // d{s,t}/d{X,Y}
+        }
+        else
+        {
+            // Fetch.
+            uvDA = ((const float4*)p.uvDA)[pidx];
+        }
+
+        // Scaling factors.
+        float uscl = p.texWidth;
+        float vscl = p.texHeight;
+
+        // d[s,t]/d[X,Y].
+        float dsdx = uvDA.x * uscl;
+        float dsdy = uvDA.y * uscl;
+        float dtdx = uvDA.z * vscl;
+        float dtdy = uvDA.w * vscl;
+
+        // Calculate footprint axis lengths.
+        float A = dsdx*dsdx + dtdx*dtdx;
+        float B = dsdy*dsdy + dtdy*dtdy;
+        float C = dsdx*dsdy + dtdx*dtdy;
+        float l2b = 0.5 * (A + B);
+        float l2n = 0.25 * (A-B)*(A-B) + C*C;
+        float l2a = sqrt(l2n);
+        float lenMinorSqr = fmaxf(0.0, l2b - l2a);
+        float lenMajorSqr = l2b + l2a;
+
+        // Footprint vs. mip level gradient.
+        if (pdw && FILTER_MODE == TEX_MODE_LINEAR_MIPMAP_LINEAR)
+        {
+            float dw   = 0.72134752f / (l2n + l2a * l2b); // Constant is 0.5/ln(2).
+            float AB   = dw * .5f * (A - B);
+            float Cw   = dw * C;
+            float l2aw = dw * l2a;
+            float d_f_ddsdX = uscl * (dsdx * (l2aw + AB) + dsdy * Cw);
+            float d_f_ddsdY = uscl * (dsdy * (l2aw - AB) + dsdx * Cw);
+            float d_f_ddtdX = vscl * (dtdx * (l2aw + AB) + dtdy * Cw);
+            float d_f_ddtdY = vscl * (dtdy * (l2aw - AB) + dtdx * Cw);
+
+            float4 d_f_dw = make_float4(d_f_ddsdX, d_f_ddsdY, d_f_ddtdX, d_f_ddtdY);
+            if (!CUBE_MODE)
+                *pdw = isfinite_vec4(d_f_dw) ? d_f_dw : make_float4(0.f, 0.f, 0.f, 0.f);
+
+            // In cube maps, there is also a texture coordinate vs. mip level gradient.
+            // Only output nonzero vectors if both are free of inf/Nan garbage.
+            if (CUBE_MODE)
+            {
+                float4 dx, dy, dz;
+                indexCubeMapGrad2(uv, dvdX, dvdY, dx, dy, dz);
+                float3 d_dsdX_dv = make_float3(dx.x, dy.x, dz.x);
+                float3 d_dsdY_dv = make_float3(dx.y, dy.y, dz.y);
+                float3 d_dtdX_dv = make_float3(dx.z, dy.z, dz.z);
+                float3 d_dtdY_dv = make_float3(dx.w, dy.w, dz.w);
+
+                float3 d_f_dv = make_float3(0.f, 0.f, 0.f);
+                d_f_dv += d_dsdX_dv * d_f_ddsdX;
+                d_f_dv += d_dsdY_dv * d_f_ddsdY;
+                d_f_dv += d_dtdX_dv * d_f_ddtdX;
+                d_f_dv += d_dtdY_dv * d_f_ddtdY;
+
+                bool finite = isfinite_vec4(d_f_dw) && isfinite_vec3(d_f_dv);
+                *pdw   = finite ? d_f_dw : make_float4(0.f, 0.f, 0.f, 0.f);
+                *pdfdv = finite ? d_f_dv : make_float3(0.f, 0.f, 0.f);
+            }
+        }
+
+        // Finally, calculate mip level.
+        flevel = .5f * __log2f(lenMajorSqr); // May be inf/NaN, but clamp fixes it.
+    }
+
+    // Bias the mip level and clamp.
+    if (p.mipLevelBias)
+        flevel += p.mipLevelBias[pidx];
+    flevel = fminf(fmaxf(flevel, 0.f), (float)p.mipLevelMax);
+
+    // Calculate levels depending on filter mode.
+    level0 = __float2int_rd(flevel);
+
+    // Leave everything else at zero if flevel == 0 (magnification) or when in linear-mipmap-nearest mode.
+    if (FILTER_MODE == TEX_MODE_LINEAR_MIPMAP_LINEAR && flevel > 0.f)
+    {
+        level1 = min(level0 + 1, p.mipLevelMax);
+        flevel -= level0; // Fractional part. Zero if clamped on last level.
+    }
+}
+
+//------------------------------------------------------------------------
+// Texel fetch and accumulator helpers that understand cube map corners.
+
+template<class T>
+static __device__ __forceinline__ void fetchQuad(T& a00, T& a10, T& a01, T& a11, const float* pIn, int4 tc, bool corner)
+{
+    // For invalid cube map uv, tc will be all negative, and all texel values will be zero.
+    if (corner)
+    {
+        T avg = zero_value<T>();
+        if (tc.x >= 0) avg += (a00 = *((const T*)&pIn[tc.x]));
+        if (tc.y >= 0) avg += (a10 = *((const T*)&pIn[tc.y]));
+        if (tc.z >= 0) avg += (a01 = *((const T*)&pIn[tc.z]));
+        if (tc.w >= 0) avg += (a11 = *((const T*)&pIn[tc.w]));
+        avg *= 0.33333333f;
+        if (tc.x < 0) a00 = avg;
+        if (tc.y < 0) a10 = avg;
+        if (tc.z < 0) a01 = avg;
+        if (tc.w < 0) a11 = avg;
+    }
+    else
+    {
+        a00 = (tc.x >= 0) ? *((const T*)&pIn[tc.x]) : zero_value<T>();
+        a10 = (tc.y >= 0) ? *((const T*)&pIn[tc.y]) : zero_value<T>();
+        a01 = (tc.z >= 0) ? *((const T*)&pIn[tc.z]) : zero_value<T>();
+        a11 = (tc.w >= 0) ? *((const T*)&pIn[tc.w]) : zero_value<T>();
+    }
+}
+
+static __device__ __forceinline__ void accumQuad(float4 c, float* pOut, int level, int4 tc, bool corner, CA_TEMP_PARAM)
+{
+    // For invalid cube map uv, tc will be all negative, and no accumulation will take place.
+    if (corner)
+    {
+        float cb;
+        if (tc.x < 0) cb = c.x;
+        if (tc.y < 0) cb = c.y;
+        if (tc.z < 0) cb = c.z;
+        if (tc.w < 0) cb = c.w;
+        cb *= 0.33333333f;
+        if (tc.x >= 0) caAtomicAddTexture(pOut, level, tc.x, c.x + cb);
+        if (tc.y >= 0) caAtomicAddTexture(pOut, level, tc.y, c.y + cb);
+        if (tc.z >= 0) caAtomicAddTexture(pOut, level, tc.z, c.z + cb);
+        if (tc.w >= 0) caAtomicAddTexture(pOut, level, tc.w, c.w + cb);
+    }
+    else
+    {
+        if (tc.x >= 0) caAtomicAddTexture(pOut, level, tc.x, c.x);
+        if (tc.y >= 0) caAtomicAddTexture(pOut, level, tc.y, c.y);
+        if (tc.z >= 0) caAtomicAddTexture(pOut, level, tc.z, c.z);
+        if (tc.w >= 0) caAtomicAddTexture(pOut, level, tc.w, c.w);
+    }
+}
+
+//------------------------------------------------------------------------
+// Mip builder kernel.
+
+template<class T, int C>
+static __forceinline__ __device__ void MipBuildKernelTemplate(const TextureKernelParams p)
+{
+    // Sizes.
+    int2 sz_in = mipLevelSize(p, p.mipLevelOut - 1);
+    int2 sz_out = mipLevelSize(p, p.mipLevelOut);
+
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    if (px >= sz_out.x || py >= sz_out.y)
+        return;
+
+    // Pixel indices.
+    int pidx_in0 = p.channels * (((px + sz_in.x * py) << 1) + (pz * sz_in.x * sz_in.y));
+    int pidx_in1 = pidx_in0 + p.channels * sz_in.x; // Next pixel down.
+    int pidx_out = p.channels * (px + sz_out.x * (py + sz_out.y * pz));
+
+    // Input and output pointers.
+    const float* pin = p.tex[p.mipLevelOut - 1];
+    float* pout = (float*)p.tex[p.mipLevelOut];
+
+    // Special case: Input texture height or width is 1.
+    if (sz_in.x == 1 || sz_in.y == 1)
+    {
+        if (sz_in.y == 1)
+            pidx_in1 = pidx_in0 + p.channels; // Next pixel on the right.
+
+        for (int i=0; i < p.channels; i += C)
+        {
+            T v0 = *((const T*)&pin[pidx_in0 + i]);
+            T v1 = *((const T*)&pin[pidx_in1 + i]);
+            T avg = .5f * (v0 + v1);
+#if TEX_DEBUG_MIP_RETAIN_VARIANCE
+            avg = (avg - .5f) * 1.41421356f + .5f;
+#endif
+            *((T*)&pout[pidx_out + i]) = avg;
+        }
+
+        return;
+    }
+
+    for (int i=0; i < p.channels; i += C)
+    {
+        T v0 = *((const T*)&pin[pidx_in0 + i]);
+        T v1 = *((const T*)&pin[pidx_in0 + i + p.channels]);
+        T v2 = *((const T*)&pin[pidx_in1 + i]);
+        T v3 = *((const T*)&pin[pidx_in1 + i + p.channels]);
+        T avg = .25f * (v0 + v1 + v2 + v3);
+#if TEX_DEBUG_MIP_RETAIN_VARIANCE
+        avg = (avg - .5f) * 2.f + .5f;
+#endif
+        *((T*)&pout[pidx_out + i]) = avg;
+    }
+}
+
+// Template specializations.
+__global__ void MipBuildKernel1(const TextureKernelParams p) { MipBuildKernelTemplate<float,  1>(p); }
+__global__ void MipBuildKernel2(const TextureKernelParams p) { MipBuildKernelTemplate<float2, 2>(p); }
+__global__ void MipBuildKernel4(const TextureKernelParams p) { MipBuildKernelTemplate<float4, 4>(p); }
+
+//------------------------------------------------------------------------
+// Forward kernel.
+
+template <class T, int C, bool CUBE_MODE, bool BIAS_ONLY, int FILTER_MODE>
+static __forceinline__ __device__ void TextureFwdKernelTemplate(const TextureKernelParams p)
+{
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    int tz = (p.texDepth == 1) ? 0 : pz;
+    if (px >= p.imgWidth || py >= p.imgHeight || pz >= p.n)
+        return;
+
+    // Pixel index.
+    int pidx = px + p.imgWidth * (py + p.imgHeight * pz);
+
+    // Output ptr.
+    float* pOut = p.out + pidx * p.channels;
+
+    // Get UV.
+    float3 uv;
+    if (CUBE_MODE)
+        uv = ((const float3*)p.uv)[pidx];
+    else
+        uv = make_float3(((const float2*)p.uv)[pidx], 0.f);
+
+    // Nearest mode.
+    if (FILTER_MODE == TEX_MODE_NEAREST)
+    {
+        int tc = indexTextureNearest<CUBE_MODE>(p, uv, tz);
+        tc *= p.channels;
+        const float* pIn = p.tex[0];
+
+        // Copy if valid tc, otherwise output zero.
+        for (int i=0; i < p.channels; i += C)
+            *((T*)&pOut[i]) = (tc >= 0) ? *((const T*)&pIn[tc + i]) : zero_value<T>();
+
+        return; // Exit.
+    }
+
+    // Calculate mip level. In 'linear' mode these will all stay zero.
+    float  flevel = 0.f; // Fractional level.
+    int    level0 = 0;   // Discrete level 0.
+    int    level1 = 0;   // Discrete level 1.
+    calculateMipLevel<CUBE_MODE, BIAS_ONLY, FILTER_MODE>(level0, level1, flevel, p, pidx, uv, 0, 0);
+
+    // Get texel indices and pointer for level 0.
+    int4 tc0 = make_int4(0, 0, 0, 0);
+    float2 uv0 = indexTextureLinear<CUBE_MODE>(p, uv, tz, tc0, level0);
+    const float* pIn0 = p.tex[level0];
+    bool corner0 = CUBE_MODE && ((tc0.x | tc0.y | tc0.z | tc0.w) < 0);
+    tc0 *= p.channels;
+
+    // Bilinear fetch.
+    if (FILTER_MODE == TEX_MODE_LINEAR || FILTER_MODE == TEX_MODE_LINEAR_MIPMAP_NEAREST)
+    {
+        // Interpolate.
+        for (int i=0; i < p.channels; i += C, tc0 += C)
+        {
+            T a00, a10, a01, a11;
+            fetchQuad<T>(a00, a10, a01, a11, pIn0, tc0, corner0);
+            *((T*)&pOut[i]) = bilerp(a00, a10, a01, a11, uv0);
+        }
+        return; // Exit.
+    }
+
+    // Get texel indices and pointer for level 1.
+    int4 tc1 = make_int4(0, 0, 0, 0);
+    float2 uv1 = indexTextureLinear<CUBE_MODE>(p, uv, tz, tc1, level1);
+    const float* pIn1 = p.tex[level1];
+    bool corner1 = CUBE_MODE && ((tc1.x | tc1.y | tc1.z | tc1.w) < 0);
+    tc1 *= p.channels;
+
+    // Trilinear fetch.
+    for (int i=0; i < p.channels; i += C, tc0 += C, tc1 += C)
+    {
+        // First level.
+        T a00, a10, a01, a11;
+        fetchQuad<T>(a00, a10, a01, a11, pIn0, tc0, corner0);
+        T a = bilerp(a00, a10, a01, a11, uv0);
+
+        // Second level unless in magnification mode.
+        if (flevel > 0.f)
+        {
+            T b00, b10, b01, b11;
+            fetchQuad<T>(b00, b10, b01, b11, pIn1, tc1, corner1);
+            T b = bilerp(b00, b10, b01, b11, uv1);
+            a = lerp(a, b, flevel); // Interpolate between levels.
+        }
+
+        // Write.
+        *((T*)&pOut[i]) = a;
+    }
+}
+
+// Template specializations.
+__global__ void TextureFwdKernelNearest1                    (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, false, false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureFwdKernelNearest2                    (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, false, false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureFwdKernelNearest4                    (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, false, false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureFwdKernelLinear1                     (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, false, false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureFwdKernelLinear2                     (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, false, false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureFwdKernelLinear4                     (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, false, false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureFwdKernelLinearMipmapNearest1        (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, false, false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelLinearMipmapNearest2        (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, false, false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelLinearMipmapNearest4        (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, false, false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelLinearMipmapLinear1         (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, false, false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelLinearMipmapLinear2         (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, false, false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelLinearMipmapLinear4         (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, false, false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeNearest1                (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, true,  false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeNearest2                (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, true,  false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeNearest4                (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, true,  false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeLinear1                 (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, true,  false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinear2                 (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, true,  false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinear4                 (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, true,  false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapNearest1    (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, true,  false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapNearest2    (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, true,  false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapNearest4    (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, true,  false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapLinear1     (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, true,  false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapLinear2     (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, true,  false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapLinear4     (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, true,  false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelLinearMipmapNearestBO1      (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, false, true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelLinearMipmapNearestBO2      (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, false, true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelLinearMipmapNearestBO4      (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, false, true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelLinearMipmapLinearBO1       (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, false, true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelLinearMipmapLinearBO2       (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, false, true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelLinearMipmapLinearBO4       (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, false, true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapNearestBO1  (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, true,  true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapNearestBO2  (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, true,  true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapNearestBO4  (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, true,  true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapLinearBO1   (const TextureKernelParams p) { TextureFwdKernelTemplate<float,  1, true,  true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapLinearBO2   (const TextureKernelParams p) { TextureFwdKernelTemplate<float2, 2, true,  true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureFwdKernelCubeLinearMipmapLinearBO4   (const TextureKernelParams p) { TextureFwdKernelTemplate<float4, 4, true,  true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+
+//------------------------------------------------------------------------
+// Gradient mip puller kernel.
+
+template<class T, int C>
+static __forceinline__ __device__ void MipGradKernelTemplate(const TextureKernelParams p)
+{
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    if (px >= p.texWidth || py >= p.texHeight)
+        return;
+
+    // Number of wide elements.
+    int c = p.channels;
+    if (C == 2) c >>= 1;
+    if (C == 4) c >>= 2;
+
+    // Dynamically allocated shared memory for holding a texel.
+    extern __shared__ float s_texelAccum[];
+    int sharedOfs = threadIdx.x + threadIdx.y * blockDim.x;
+    int sharedStride = blockDim.x * blockDim.y;
+#   define TEXEL_ACCUM(_i) (s_texelAccum + (sharedOfs + (_i) * sharedStride))
+
+    // Clear the texel.
+    for (int i=0; i < p.channels; i++)
+        *TEXEL_ACCUM(i) = 0.f;
+
+    // Track texel position and accumulation weight over the mip stack.
+    int x = px;
+    int y = py;
+    float w = 1.f;
+
+    // Pull gradients from all levels.
+    int2 sz = mipLevelSize(p, 0); // Previous level size.
+    for (int level=1; level <= p.mipLevelMax; level++)
+    {
+        // Weight decay depends on previous level size.
+        if (sz.x > 1) w *= .5f;
+        if (sz.y > 1) w *= .5f;
+
+        // Current level size and coordinates.
+        sz = mipLevelSize(p, level);
+        x >>= 1;
+        y >>= 1;
+
+        T* pIn = (T*)(p.gradTex[level] + (x + sz.x * (y + sz.y * pz)) * p.channels);
+        for (int i=0; i < c; i++)
+            accum_from_mem(TEXEL_ACCUM(i * C), sharedStride, pIn[i], w);
+    }
+
+    // Add to main texture gradients.
+    T* pOut = (T*)(p.gradTex[0] + (px + p.texWidth * (py + p.texHeight * pz)) * p.channels);
+    for (int i=0; i < c; i++)
+        accum_to_mem(pOut[i], TEXEL_ACCUM(i * C), sharedStride);
+}
+
+// Template specializations.
+__global__ void MipGradKernel1(const TextureKernelParams p) { MipGradKernelTemplate<float,  1>(p); }
+__global__ void MipGradKernel2(const TextureKernelParams p) { MipGradKernelTemplate<float2, 2>(p); }
+__global__ void MipGradKernel4(const TextureKernelParams p) { MipGradKernelTemplate<float4, 4>(p); }
+
+//------------------------------------------------------------------------
+// Gradient kernel.
+
+template <bool CUBE_MODE, bool BIAS_ONLY, int FILTER_MODE>
+static __forceinline__ __device__ void TextureGradKernelTemplate(const TextureKernelParams p)
+{
+    // Temporary space for coalesced atomics.
+    CA_DECLARE_TEMP(TEX_GRAD_MAX_KERNEL_BLOCK_WIDTH * TEX_GRAD_MAX_KERNEL_BLOCK_HEIGHT);
+
+    // Calculate pixel position.
+    int px = blockIdx.x * blockDim.x + threadIdx.x;
+    int py = blockIdx.y * blockDim.y + threadIdx.y;
+    int pz = blockIdx.z;
+    int tz = (p.texDepth == 1) ? 0 : pz;
+    if (px >= p.imgWidth || py >= p.imgHeight || pz >= p.n)
+        return;
+
+    // Pixel index.
+    int pidx = px + p.imgWidth * (py + p.imgHeight * pz);
+
+    // Early exit if output gradients are zero.
+    const float* pDy = p.dy + pidx * p.channels;
+    unsigned int dmax = 0u;
+    if ((p.channels & 3) == 0)
+    {
+        for (int i=0; i < p.channels; i += 4)
+        {
+            uint4 dy = *((const uint4*)&pDy[i]);
+            dmax |= (dy.x | dy.y | dy.z | dy.w);
+        }
+    }
+    else
+    {
+        for (int i=0; i < p.channels; i++)
+            dmax |= __float_as_uint(pDy[i]);
+    }
+
+    // Store zeros and exit.
+    if (__uint_as_float(dmax) == 0.f)
+    {
+        if (CUBE_MODE)
+        {
+            if (FILTER_MODE != TEX_MODE_NEAREST)
+                ((float3*)p.gradUV)[pidx] = make_float3(0.f, 0.f, 0.f);
+            if (FILTER_MODE == TEX_MODE_LINEAR_MIPMAP_LINEAR)
+            {
+                if (p.gradUVDA)
+                {
+                    ((float2*)p.gradUVDA)[3 * pidx + 0] = make_float2(0.f, 0.f);
+                    ((float2*)p.gradUVDA)[3 * pidx + 1] = make_float2(0.f, 0.f);
+                    ((float2*)p.gradUVDA)[3 * pidx + 2] = make_float2(0.f, 0.f);
+                }
+                if (p.gradMipLevelBias)
+                    p.gradMipLevelBias[pidx] = 0.f;
+            }
+        }
+        else
+        {
+            if (FILTER_MODE != TEX_MODE_NEAREST)
+                ((float2*)p.gradUV)[pidx] = make_float2(0.f, 0.f);
+            if (FILTER_MODE == TEX_MODE_LINEAR_MIPMAP_LINEAR)
+            {
+                if (p.gradUVDA)
+                    ((float4*)p.gradUVDA)[pidx] = make_float4(0.f, 0.f, 0.f, 0.f);
+                if (p.gradMipLevelBias)
+                    p.gradMipLevelBias[pidx] = 0.f;
+            }
+        }
+        return;
+    }
+
+    // Get UV.
+    float3 uv;
+    if (CUBE_MODE)
+        uv = ((const float3*)p.uv)[pidx];
+    else
+        uv = make_float3(((const float2*)p.uv)[pidx], 0.f);
+
+    // Nearest mode - texture gradients only.
+    if (FILTER_MODE == TEX_MODE_NEAREST)
+    {
+        int tc = indexTextureNearest<CUBE_MODE>(p, uv, tz);
+        if (tc < 0)
+            return; // Outside texture.
+
+        tc *= p.channels;
+        float* pOut = p.gradTex[0];
+
+        // Accumulate texture gradients.
+        for (int i=0; i < p.channels; i++)
+            caAtomicAddTexture(pOut, 0, tc + i, pDy[i]);
+
+        return; // Exit.
+    }
+
+    // Calculate mip level. In 'linear' mode these will all stay zero.
+    float4 dw = make_float4(0.f, 0.f, 0.f, 0.f);
+    float3 dfdv = make_float3(0.f, 0.f, 0.f);
+    float  flevel = 0.f; // Fractional level.
+    int    level0 = 0;   // Discrete level 0.
+    int    level1 = 0;   // Discrete level 1.
+    calculateMipLevel<CUBE_MODE, BIAS_ONLY, FILTER_MODE>(level0, level1, flevel, p, pidx, uv, &dw, &dfdv);
+
+    // UV gradient accumulators.
+    float gu = 0.f;
+    float gv = 0.f;
+
+    // Get texel indices and pointers for level 0.
+    int4 tc0 = make_int4(0, 0, 0, 0);
+    float2 uv0 = indexTextureLinear<CUBE_MODE>(p, uv, tz, tc0, level0);
+    const float* pIn0 = p.tex[level0];
+    float* pOut0 = p.gradTex[level0];
+    bool corner0 = CUBE_MODE && ((tc0.x | tc0.y | tc0.z | tc0.w) < 0);
+    tc0 *= p.channels;
+
+    // Texel weights.
+    float uv011 = uv0.x * uv0.y;
+    float uv010 = uv0.x - uv011;
+    float uv001 = uv0.y - uv011;
+    float uv000 = 1.f - uv0.x - uv001;
+    float4 tw0 = make_float4(uv000, uv010, uv001, uv011);
+
+    // Attribute weights.
+    int2 sz0 = mipLevelSize(p, level0);
+    float sclu0 = (float)sz0.x;
+    float sclv0 = (float)sz0.y;
+
+    // Bilinear mode - texture and uv gradients.
+    if (FILTER_MODE == TEX_MODE_LINEAR || FILTER_MODE == TEX_MODE_LINEAR_MIPMAP_NEAREST)
+    {
+        for (int i=0; i < p.channels; i++, tc0 += 1)
+        {
+            float dy = pDy[i];
+            accumQuad(tw0 * dy, pOut0, level0, tc0, corner0, CA_TEMP);
+
+            float a00, a10, a01, a11;
+            fetchQuad<float>(a00, a10, a01, a11, pIn0, tc0, corner0);
+            float ad = (a11 + a00 - a10 - a01);
+            gu += dy * ((a10 - a00) + uv0.y * ad) * sclu0;
+            gv += dy * ((a01 - a00) + uv0.x * ad) * sclv0;
+        }
+
+        // Store UV gradients and exit.
+        if (CUBE_MODE)
+            ((float3*)p.gradUV)[pidx] = indexCubeMapGrad(uv, gu, gv);
+        else
+            ((float2*)p.gradUV)[pidx] = make_float2(gu, gv);
+
+        return;
+    }
+
+    // Accumulate fractional mip level gradient.
+    float df = 0; // dL/df.
+
+    // Get texel indices and pointers for level 1.
+    int4 tc1 = make_int4(0, 0, 0, 0);
+    float2 uv1 = indexTextureLinear<CUBE_MODE>(p, uv, tz, tc1, level1);
+    const float* pIn1 = p.tex[level1];
+    float* pOut1 = p.gradTex[level1];
+    bool corner1 = CUBE_MODE && ((tc1.x | tc1.y | tc1.z | tc1.w) < 0);
+    tc1 *= p.channels;
+
+    // Texel weights.
+    float uv111 = uv1.x * uv1.y;
+    float uv110 = uv1.x - uv111;
+    float uv101 = uv1.y - uv111;
+    float uv100 = 1.f - uv1.x - uv101;
+    float4 tw1 = make_float4(uv100, uv110, uv101, uv111);
+
+    // Attribute weights.
+    int2 sz1 = mipLevelSize(p, level1);
+    float sclu1 = (float)sz1.x;
+    float sclv1 = (float)sz1.y;
+
+    // Trilinear mode.
+    for (int i=0; i < p.channels; i++, tc0 += 1, tc1 += 1)
+    {
+        float dy = pDy[i];
+        float dy0 = (1.f - flevel) * dy;
+        accumQuad(tw0 * dy0, pOut0, level0, tc0, corner0, CA_TEMP);
+
+        // UV gradients for first level.
+        float a00, a10, a01, a11;
+        fetchQuad<float>(a00, a10, a01, a11, pIn0, tc0, corner0);
+        float ad = (a11 + a00 - a10 - a01);
+        gu += dy0 * ((a10 - a00) + uv0.y * ad) * sclu0;
+        gv += dy0 * ((a01 - a00) + uv0.x * ad) * sclv0;
+
+        // Second level unless in magnification mode.
+        if (flevel > 0.f)
+        {
+            // Texture gradients for second level.
+            float dy1 = flevel * dy;
+            accumQuad(tw1 * dy1, pOut1, level1, tc1, corner1, CA_TEMP);
+
+            // UV gradients for second level.
+            float b00, b10, b01, b11;
+            fetchQuad<float>(b00, b10, b01, b11, pIn1, tc1, corner1);
+            float bd = (b11 + b00 - b10 - b01);
+            gu += dy1 * ((b10 - b00) + uv1.y * bd) * sclu1;
+            gv += dy1 * ((b01 - b00) + uv1.x * bd) * sclv1;
+
+            // Mip level gradient.
+            float a = bilerp(a00, a10, a01, a11, uv0);
+            float b = bilerp(b00, b10, b01, b11, uv1);
+            df += (b-a) * dy;
+        }
+    }
+
+    // Store UV gradients.
+    if (CUBE_MODE)
+        ((float3*)p.gradUV)[pidx] = indexCubeMapGrad(uv, gu, gv) + (dfdv * df);
+    else
+        ((float2*)p.gradUV)[pidx] = make_float2(gu, gv);
+
+    // Store mip level bias gradient.
+    if (p.gradMipLevelBias)
+        p.gradMipLevelBias[pidx] = df;
+
+    // Store UV pixel differential gradients.
+    if (!BIAS_ONLY)
+    {
+        // Final gradients.
+        dw *= df; // dL/(d{s,y}/d{X,Y}) = df/(d{s,y}/d{X,Y}) * dL/df.
+
+        // Store them.
+        if (CUBE_MODE)
+        {
+            // Remap from dL/(d{s,t}/s{X,Y}) to dL/(d{x,y,z}/d{X,Y}).
+            float3 g0, g1;
+            indexCubeMapGrad4(uv, dw, g0, g1);
+            ((float2*)p.gradUVDA)[3 * pidx + 0] = make_float2(g0.x, g1.x);
+            ((float2*)p.gradUVDA)[3 * pidx + 1] = make_float2(g0.y, g1.y);
+            ((float2*)p.gradUVDA)[3 * pidx + 2] = make_float2(g0.z, g1.z);
+        }
+        else
+            ((float4*)p.gradUVDA)[pidx] = dw;
+    }
+}
+
+// Template specializations.
+__global__ void TextureGradKernelNearest                    (const TextureKernelParams p) { TextureGradKernelTemplate<false, false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureGradKernelLinear                     (const TextureKernelParams p) { TextureGradKernelTemplate<false, false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureGradKernelLinearMipmapNearest        (const TextureKernelParams p) { TextureGradKernelTemplate<false, false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureGradKernelLinearMipmapLinear         (const TextureKernelParams p) { TextureGradKernelTemplate<false, false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureGradKernelCubeNearest                (const TextureKernelParams p) { TextureGradKernelTemplate<true,  false, TEX_MODE_NEAREST>(p); }
+__global__ void TextureGradKernelCubeLinear                 (const TextureKernelParams p) { TextureGradKernelTemplate<true,  false, TEX_MODE_LINEAR>(p); }
+__global__ void TextureGradKernelCubeLinearMipmapNearest    (const TextureKernelParams p) { TextureGradKernelTemplate<true,  false, TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureGradKernelCubeLinearMipmapLinear     (const TextureKernelParams p) { TextureGradKernelTemplate<true,  false, TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureGradKernelLinearMipmapNearestBO      (const TextureKernelParams p) { TextureGradKernelTemplate<false, true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureGradKernelLinearMipmapLinearBO       (const TextureKernelParams p) { TextureGradKernelTemplate<false, true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+__global__ void TextureGradKernelCubeLinearMipmapNearestBO  (const TextureKernelParams p) { TextureGradKernelTemplate<true,  true,  TEX_MODE_LINEAR_MIPMAP_NEAREST>(p); }
+__global__ void TextureGradKernelCubeLinearMipmapLinearBO   (const TextureKernelParams p) { TextureGradKernelTemplate<true,  true,  TEX_MODE_LINEAR_MIPMAP_LINEAR>(p); }
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/lib/setgpu.lib b/extensions/nvdiffrast/nvdiffrast/lib/setgpu.lib
new file mode 100644
index 0000000000000000000000000000000000000000..add9a0c4f631cb56dbee31a05ed97339930301e2
Binary files /dev/null and b/extensions/nvdiffrast/nvdiffrast/lib/setgpu.lib differ
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/__init__.py b/extensions/nvdiffrast/nvdiffrast/tensorflow/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..cf62df8782d730f072ca5f4e4862a44dc8c3a086
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/__init__.py
@@ -0,0 +1,12 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+from .ops import rasterize, interpolate, texture, antialias
+from .plugin_loader import set_cache_dir
+
+__all__ = ["rasterize", "interpolate", "texture", "antialias", "set_cache_dir"]
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/ops.py b/extensions/nvdiffrast/nvdiffrast/tensorflow/ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..be51deef13e0ecfbd5bfe8bc376af24a18db7224
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/ops.py
@@ -0,0 +1,303 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+import tensorflow as tf
+import numpy as np
+import os
+from . import plugin_loader
+
+#----------------------------------------------------------------------------
+# Helpers.
+#----------------------------------------------------------------------------
+
+# OpenGL-related linker options depending on platform.
+def _get_gl_opts():
+    libs = {
+        'posix': ['GL', 'EGL'],
+        'nt':    ['gdi32', 'opengl32', 'user32', 'setgpu'],
+    }
+    return ['-l' + x for x in libs[os.name]]
+
+# Load the cpp plugin.
+def _get_plugin():
+    fn = os.path.join(os.path.dirname(__file__), 'tf_all.cu')
+    return plugin_loader.get_plugin(fn, extra_nvcc_options=_get_gl_opts() + ['-DNVDR_TENSORFLOW'])
+
+# Convert parameter to a numpy array if possible.
+def _get_constant(x, dtype):
+    try:
+        return np.asarray(x, dtype=dtype)
+    except (TypeError, ValueError):
+        return None
+
+# Tests for a construction-time constantness instead of tf.constant node because
+# the latter can be overridden in Session.run() feed_dict at evaluation time.
+def _is_constant(x, dtype):
+    if isinstance(x, np.ndarray):
+        return np.can_cast(x.dtype, dtype, 'unsafe')
+    else:
+        return _get_constant(x, dtype) is not None
+
+#----------------------------------------------------------------------------
+# Rasterize.
+#----------------------------------------------------------------------------
+
+def rasterize(pos, tri, resolution, ranges=None, tri_const=False, output_db=True, grad_db=True):
+    assert tri_const is True or tri_const is False
+    assert output_db is True or output_db is False
+
+    # Known constant resolution?
+    resolution_c = _get_constant(resolution, np.int32)
+
+    # Known constant triangles?
+    tri_const = tri_const or _is_constant(tri, np.int32)
+
+    # Convert all inputs to tensors / base types.
+    tri_const = 1 if tri_const else 0
+    tri = tf.convert_to_tensor(tri, dtype=tf.int32)
+    pos = tf.convert_to_tensor(pos, dtype=tf.float32)
+    resolution = tf.convert_to_tensor(resolution, dtype=tf.int32)
+    if ranges is None:
+        ranges = tf.convert_to_tensor(np.zeros(shape=[0, 2], dtype=np.int32)) # Empty tensor.
+    else:
+        ranges = tf.convert_to_tensor(ranges, dtype=tf.int32) # Convert input to tensor.
+
+    # Infer as much about the output shape as possible.
+    out_shape = [None, None, None, 4]
+    if pos.shape.rank == 3: # Instanced mode.
+        out_shape[0] = pos.shape[0].value
+    elif pos.shape.rank == 2: # Range mode.
+        if ranges.shape.rank not in [None, 0]:
+            out_shape[0] = ranges.shape[0].value
+    if resolution_c is not None:
+        assert resolution_c.shape == (2,)
+        out_shape[1], out_shape[2] = resolution_c
+
+    # Output pixel differentials.
+    @tf.custom_gradient
+    def func_db(pos):
+        out, out_db = _get_plugin().rasterize_fwd(pos, tri, resolution, ranges, 1, tri_const)
+        out.set_shape(out_shape)
+        out_db.set_shape(out_shape)
+        def grad(dy, ddb):
+            if grad_db:
+                return _get_plugin().rasterize_grad_db(pos, tri, out, dy, ddb)
+            else:
+                return _get_plugin().rasterize_grad(pos, tri, out, dy)
+        return (out, out_db), grad
+
+    # Do not output pixel differentials.
+    @tf.custom_gradient
+    def func(pos):
+        out, out_db = _get_plugin().rasterize_fwd(pos, tri, resolution, ranges, 0, tri_const)
+        out.set_shape(out_shape)
+        out_db.set_shape(out_shape[:-1] + [0]) # Zero channels in out_db.
+        def grad(dy, _):
+            return _get_plugin().rasterize_grad(pos, tri, out, dy)
+        return (out, out_db), grad
+
+    # Choose stub.
+    if output_db:
+        return func_db(pos)
+    else:
+        return func(pos)
+
+#----------------------------------------------------------------------------
+# Interpolate.
+#----------------------------------------------------------------------------
+
+def interpolate(attr, rast, tri, rast_db=None, diff_attrs=None):
+    # Sanitize the list of pixel differential attributes.
+    if diff_attrs is None:
+        diff_attrs = []
+    elif diff_attrs != 'all':
+        diff_attrs = _get_constant(diff_attrs, np.int32)
+        assert (diff_attrs is not None) and len(diff_attrs.shape) == 1
+        diff_attrs = diff_attrs.tolist()
+
+    # Convert all inputs to tensors.
+    attr = tf.convert_to_tensor(attr, dtype=tf.float32)
+    rast = tf.convert_to_tensor(rast, dtype=tf.float32)
+    tri = tf.convert_to_tensor(tri, dtype=tf.int32)
+    if diff_attrs:
+        rast_db = tf.convert_to_tensor(rast_db, dtype=tf.float32)
+
+    # Infer output shape.
+    out_shape = [None, None, None, None]
+    if rast.shape.rank is not None:
+        out_shape = [rast.shape[0].value, rast.shape[1].value, rast.shape[2].value, None]
+    if attr.shape.rank in [2, 3]:
+        out_shape[3] = attr.shape[-1].value
+
+    # Output pixel differentials for at least some attributes.
+    @tf.custom_gradient
+    def func_da(attr, rast, rast_db):
+        diff_attrs_all = int(diff_attrs == 'all')
+        diff_attrs_list = [] if diff_attrs_all else diff_attrs
+        out, out_da = _get_plugin().interpolate_fwd_da(attr, rast, tri, rast_db, diff_attrs_all, diff_attrs_list)
+
+        # Infer number of channels in out_da.
+        if not diff_attrs_all:
+            da_channels = 2 * len(diff_attrs)
+        if (attr.shape.rank in [2, 3]) and (attr.shape[-1].value is not None):
+            da_channels = 2 * attr.shape[-1].value
+        else:
+            da_channels = None
+
+        # Set output shapes.
+        out.set_shape(out_shape)
+        out_da.set_shape([out_shape[0], out_shape[1], out_shape[2], da_channels])
+
+        def grad(dy, dda):
+            return _get_plugin().interpolate_grad_da(attr, rast, tri, dy, rast_db, dda, diff_attrs_all, diff_attrs_list)
+        return (out, out_da), grad
+
+    # No pixel differentials for any attribute.
+    @tf.custom_gradient
+    def func(attr, rast):
+        out, out_da = _get_plugin().interpolate_fwd(attr, rast, tri)
+        out.set_shape(out_shape)
+        out_da.set_shape(out_shape[:-1] + [0]) # Zero channels in out_da.
+        def grad(dy, _):
+            return _get_plugin().interpolate_grad(attr, rast, tri, dy)
+        return (out, out_da), grad
+
+    # Choose stub.
+    if diff_attrs:
+        return func_da(attr, rast, rast_db)
+    else:
+        return func(attr, rast)
+
+#----------------------------------------------------------------------------
+# Texture.
+#----------------------------------------------------------------------------
+
+def texture(tex, uv, uv_da=None, filter_mode='auto', boundary_mode='wrap', tex_const=False, max_mip_level=None):
+    assert tex_const is True or tex_const is False
+
+    # Default filter mode.
+    if filter_mode == 'auto':
+        filter_mode = 'linear-mipmap-linear' if (uv_da is not None) else 'linear'
+
+    # Known constant texture?
+    tex_const = tex_const or _is_constant(tex, np.float32)
+
+    # Sanitize inputs.
+    tex_const = 1 if tex_const else 0
+    if max_mip_level is None:
+        max_mip_level = -1
+    else:
+        max_mip_level = int(max_mip_level)
+        assert max_mip_level >= 0
+
+    # Convert inputs to tensors.
+    tex = tf.convert_to_tensor(tex, dtype=tf.float32)
+    uv = tf.convert_to_tensor(uv, dtype=tf.float32)
+    if 'mipmap' in filter_mode:
+        uv_da = tf.convert_to_tensor(uv_da, dtype=tf.float32)
+
+    # Infer output shape.
+    out_shape = [None, None, None, None]
+    if uv.shape.rank is not None:
+        assert uv.shape.rank == 4
+        out_shape = [uv.shape[0].value, uv.shape[1].value, uv.shape[2].value, None]
+    if tex.shape.rank is not None:
+        assert tex.shape.rank == (5 if boundary_mode == 'cube' else 4)
+        out_shape[-1] = tex.shape[-1].value
+
+    # If mipping disabled via max level=0, we may as well use simpler filtering internally.
+    if max_mip_level == 0 and filter_mode in ['linear-mipmap-nearest', 'linear-mipmap-linear']:
+        filter_mode = 'linear'
+
+    # Convert filter mode to internal enumeration.
+    filter_mode_dict = {'nearest': 0, 'linear': 1, 'linear-mipmap-nearest': 2, 'linear-mipmap-linear': 3}
+    filter_mode_enum = filter_mode_dict[filter_mode]
+
+    # Convert boundary mode to internal enumeration.
+    boundary_mode_dict = {'cube': 0, 'wrap': 1, 'clamp': 2, 'zero': 3}
+    boundary_mode_enum = boundary_mode_dict[boundary_mode]
+
+    # Linear-mipmap-linear: Mipmaps enabled, all gradients active.
+    @tf.custom_gradient
+    def func_linear_mipmap_linear(tex, uv, uv_da):
+        out, mip = _get_plugin().texture_fwd_mip(tex, uv, uv_da, filter_mode_enum, boundary_mode_enum, tex_const, max_mip_level)
+        out.set_shape(out_shape)
+        def grad(dy):
+            return _get_plugin().texture_grad_linear_mipmap_linear(tex, uv, dy, uv_da, mip, filter_mode_enum, boundary_mode_enum, max_mip_level)
+        return out, grad
+
+    # Linear-mipmap-nearest: Mipmaps enabled, no gradients to uv_da.
+    @tf.custom_gradient
+    def func_linear_mipmap_nearest(tex, uv):
+        out, mip = _get_plugin().texture_fwd_mip(tex, uv, uv_da, filter_mode_enum, boundary_mode_enum, tex_const, max_mip_level)
+        out.set_shape(out_shape)
+        def grad(dy):
+            return _get_plugin().texture_grad_linear_mipmap_nearest(tex, uv, dy, uv_da, mip, filter_mode_enum, boundary_mode_enum, max_mip_level)
+        return out, grad
+
+    # Linear: Mipmaps disabled, no uv_da, no gradients to uv_da.
+    @tf.custom_gradient
+    def func_linear(tex, uv):
+        out = _get_plugin().texture_fwd(tex, uv, filter_mode_enum, boundary_mode_enum)
+        out.set_shape(out_shape)
+        def grad(dy):
+            return _get_plugin().texture_grad_linear(tex, uv, dy, filter_mode_enum, boundary_mode_enum)
+        return out, grad
+
+    # Nearest: Mipmaps disabled, no uv_da, no gradients to uv_da or uv.
+    @tf.custom_gradient
+    def func_nearest(tex):
+        out = _get_plugin().texture_fwd(tex, uv, filter_mode_enum, boundary_mode_enum)
+        out.set_shape(out_shape)
+        def grad(dy):
+            return _get_plugin().texture_grad_nearest(tex, uv, dy, filter_mode_enum, boundary_mode_enum)
+        return out, grad
+
+    # Choose stub.
+    if filter_mode == 'linear-mipmap-linear':
+        return func_linear_mipmap_linear(tex, uv, uv_da)
+    elif filter_mode == 'linear-mipmap-nearest':
+        return func_linear_mipmap_nearest(tex, uv)
+    elif filter_mode == 'linear':
+        return func_linear(tex, uv)
+    elif filter_mode == 'nearest':
+        return func_nearest(tex)
+
+#----------------------------------------------------------------------------
+# Antialias.
+#----------------------------------------------------------------------------
+
+def antialias(color, rast, pos, tri, tri_const=False, pos_gradient_boost=1.0):
+    assert tri_const is True or tri_const is False
+
+    # Known constant triangles?
+    tri_const = tri_const or _is_constant(tri, np.int32)
+
+    # Convert inputs to tensors.
+    color = tf.convert_to_tensor(color, dtype=tf.float32)
+    rast = tf.convert_to_tensor(rast, dtype=tf.float32)
+    pos = tf.convert_to_tensor(pos, dtype=tf.float32)
+    tri = tf.convert_to_tensor(tri, dtype=tf.int32)
+
+    # Sanitize inputs.
+    tri_const = 1 if tri_const else 0
+
+    @tf.custom_gradient
+    def func(color, pos):
+        color_out, work_buffer = _get_plugin().antialias_fwd(color, rast, pos, tri, tri_const)
+        color_out.set_shape(color.shape)
+        def grad(dy):
+            grad_color, grad_pos = _get_plugin().antialias_grad(color, rast, pos, tri, dy, work_buffer)
+            if pos_gradient_boost != 1.0:
+                grad_pos = grad_pos * pos_gradient_boost
+            return grad_color, grad_pos
+        return color_out, grad
+
+    return func(color, pos)
+
+#----------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/plugin_loader.py b/extensions/nvdiffrast/nvdiffrast/tensorflow/plugin_loader.py
new file mode 100644
index 0000000000000000000000000000000000000000..3918aecdab6bb4192e8810bd872abf9a1fc30971
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/plugin_loader.py
@@ -0,0 +1,219 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+import glob
+import os
+import re
+import uuid
+import hashlib
+import tempfile
+import shutil
+import tensorflow as tf
+from tensorflow.python.client import device_lib # pylint: disable=no-name-in-module
+
+#----------------------------------------------------------------------------
+# Global options.
+
+_nvdiffrast_cache_dir = None
+
+def set_cache_dir(path: str) -> None:
+    '''Set CUDA kernel compilation temp dir.
+
+    If `set_cache_dir` is not called, the cache directory will default to
+    one of the below:
+
+    - Value of NVDIFFRAST_CACHE_DIR env var, if set
+    - $HOME/.cache/nvdiffrast if HOME env var is set
+    - $USERPROFILE/.cache/nvdiffrast if USERPROFILE is set.
+
+    Args:
+      path: Where to save CUDA kernel build temporaries
+    '''
+    global _nvdiffrast_cache_dir
+    _nvdiffrast_cache_dir = path
+
+def make_cache_dir_path(*paths: str) -> str:
+    if _nvdiffrast_cache_dir is not None:
+        return os.path.join(_nvdiffrast_cache_dir, *paths)
+    if 'NVDIFFRAST_CACHE_DIR' in os.environ:
+        return os.path.join(os.environ['NVDIFFRAST_CACHE_DIR'], *paths)
+    if 'HOME' in os.environ:
+        return os.path.join(os.environ['HOME'], '.cache', 'nvdiffrast', *paths)
+    if 'USERPROFILE' in os.environ:
+        return os.path.join(os.environ['USERPROFILE'], '.cache', 'nvdiffrast', *paths)
+    return os.path.join(tempfile.gettempdir(), '.cache', 'nvdiffrast', *paths)
+
+cuda_cache_version_tag = 'v1'
+do_not_hash_included_headers = False # Speed up compilation by assuming that headers included by the CUDA code never change. Unsafe!
+verbose = True # Print status messages to stdout.
+
+#----------------------------------------------------------------------------
+# Internal helper funcs.
+
+def _find_compiler_bindir():
+    hostx64_paths = sorted(glob.glob('C:/Program Files/Microsoft Visual Studio/*/Enterprise/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    hostx64_paths = sorted(glob.glob('C:/Program Files (x86)/Microsoft Visual Studio/*/Enterprise/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    hostx64_paths = sorted(glob.glob('C:/Program Files/Microsoft Visual Studio/*/Professional/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    hostx64_paths = sorted(glob.glob('C:/Program Files (x86)/Microsoft Visual Studio/*/Professional/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    hostx64_paths = sorted(glob.glob('C:/Program Files/Microsoft Visual Studio/*/BuildTools/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    hostx64_paths = sorted(glob.glob('C:/Program Files (x86)/Microsoft Visual Studio/*/BuildTools/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    hostx64_paths = sorted(glob.glob('C:/Program Files/Microsoft Visual Studio/*/Community/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    hostx64_paths = sorted(glob.glob('C:/Program Files (x86)/Microsoft Visual Studio/*/Community/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
+    if hostx64_paths != []:
+        return hostx64_paths[0]
+    vc_bin_dir = 'C:/Program Files (x86)/Microsoft Visual Studio 14.0/vc/bin'
+    if os.path.isdir(vc_bin_dir):
+        return vc_bin_dir
+    return None
+
+def _get_compute_cap(device):
+    caps_str = device.physical_device_desc
+    m = re.search('compute capability: (\\d+).(\\d+)', caps_str)
+    major = m.group(1)
+    minor = m.group(2)
+    return (major, minor)
+
+def _get_cuda_gpu_arch_string():
+    gpus = [x for x in device_lib.list_local_devices() if x.device_type == 'GPU']
+    if len(gpus) == 0:
+        raise RuntimeError('No GPU devices found')
+    (major, minor) = _get_compute_cap(gpus[0])
+    return 'sm_%s%s' % (major, minor)
+
+def _run_cmd(cmd):
+    with os.popen(cmd) as pipe:
+        output = pipe.read()
+        status = pipe.close()
+    if status is not None:
+        raise RuntimeError('NVCC returned an error. See below for full command line and output log:\n\n%s\n\n%s' % (cmd, output))
+
+def _prepare_nvcc_cli(opts):
+    cmd = 'nvcc ' + opts.strip()
+    cmd += ' --disable-warnings'
+    cmd += ' --include-path "%s"' % tf.sysconfig.get_include()
+    cmd += ' --include-path "%s"' % os.path.join(tf.sysconfig.get_include(), 'external', 'protobuf_archive', 'src')
+    cmd += ' --include-path "%s"' % os.path.join(tf.sysconfig.get_include(), 'external', 'com_google_absl')
+    cmd += ' --include-path "%s"' % os.path.join(tf.sysconfig.get_include(), 'external', 'eigen_archive')
+
+    compiler_bindir = _find_compiler_bindir()
+    if compiler_bindir is None:
+        # Require that _find_compiler_bindir succeeds on Windows.  Allow
+        # nvcc to use whatever is the default on Linux.
+        if os.name == 'nt':
+            raise RuntimeError('Could not find MSVC/GCC/CLANG installation on this computer. Check compiler_bindir_search_path list in "%s".' % __file__)
+    else:
+        cmd += ' --compiler-bindir "%s"' % compiler_bindir
+    cmd += ' 2>&1'
+    return cmd
+
+#----------------------------------------------------------------------------
+# Main entry point.
+
+_plugin_cache = dict()
+
+def get_plugin(cuda_file, extra_nvcc_options=[]):
+    cuda_file_base = os.path.basename(cuda_file)
+    cuda_file_name, cuda_file_ext = os.path.splitext(cuda_file_base)
+
+    # Already in cache?
+    if cuda_file in _plugin_cache:
+        return _plugin_cache[cuda_file]
+
+    # Setup plugin.
+    if verbose:
+        print('Setting up TensorFlow plugin "%s": ' % cuda_file_base, end='', flush=True)
+    try:
+        # Hash CUDA source.
+        md5 = hashlib.md5()
+        with open(cuda_file, 'rb') as f:
+            md5.update(f.read())
+        md5.update(b'\n')
+
+        # Hash headers included by the CUDA code by running it through the preprocessor.
+        if not do_not_hash_included_headers:
+            if verbose:
+                print('Preprocessing... ', end='', flush=True)
+            with tempfile.TemporaryDirectory() as tmp_dir:
+                tmp_file = os.path.join(tmp_dir, cuda_file_name + '_tmp' + cuda_file_ext)
+                _run_cmd(_prepare_nvcc_cli('"%s" --preprocess -o "%s" --keep --keep-dir "%s"' % (cuda_file, tmp_file, tmp_dir)))
+                with open(tmp_file, 'rb') as f:
+                    bad_file_str = ('"' + cuda_file.replace('\\', '/') + '"').encode('utf-8') # __FILE__ in error check macros
+                    good_file_str = ('"' + cuda_file_base + '"').encode('utf-8')
+                    for ln in f:
+                        if not ln.startswith(b'# ') and not ln.startswith(b'#line '): # ignore line number pragmas
+                            ln = ln.replace(bad_file_str, good_file_str)
+                            md5.update(ln)
+                    md5.update(b'\n')
+
+        # Select compiler options.
+        compile_opts = ''
+        if os.name == 'nt':
+            compile_opts += '"%s"' % os.path.join(tf.sysconfig.get_lib(), 'python', '_pywrap_tensorflow_internal.lib')
+            compile_opts += ' --library-path="%s"' % (os.path.dirname(__file__) + r"\..\lib") # Find libraries during compilation.
+        elif os.name == 'posix':
+            compile_opts += '"%s"' % os.path.join(tf.sysconfig.get_lib(), 'python', '_pywrap_tensorflow_internal.so')
+            compile_opts += ' --compiler-options \'-fPIC -D_GLIBCXX_USE_CXX11_ABI=0\''
+        else:
+            assert False # not Windows or Linux, w00t?
+        compile_opts += ' --gpu-architecture=%s' % _get_cuda_gpu_arch_string()
+        compile_opts += ' --use_fast_math'
+        for opt in extra_nvcc_options:
+            compile_opts += ' ' + opt
+        nvcc_cmd = _prepare_nvcc_cli(compile_opts)
+
+        # Hash build configuration.
+        md5.update(('nvcc_cmd: ' + nvcc_cmd).encode('utf-8') + b'\n')
+        md5.update(('tf.VERSION: ' + tf.VERSION).encode('utf-8') + b'\n')
+        md5.update(('cuda_cache_version_tag: ' + cuda_cache_version_tag).encode('utf-8') + b'\n')
+
+        # Compile if not already compiled.
+        bin_file_ext = '.dll' if os.name == 'nt' else '.so'
+        cuda_cache_path = make_cache_dir_path()
+        bin_file = os.path.join(make_cache_dir_path(), cuda_file_name + '_' + md5.hexdigest() + bin_file_ext)
+        if not os.path.isfile(bin_file):
+            if verbose:
+                print('Compiling... ', end='', flush=True)
+            with tempfile.TemporaryDirectory() as tmp_dir:
+                tmp_file = os.path.join(tmp_dir, cuda_file_name + '_tmp' + bin_file_ext)
+                _run_cmd(nvcc_cmd + ' "%s" --shared -o "%s" --keep --keep-dir "%s"' % (cuda_file, tmp_file, tmp_dir))
+                os.makedirs(cuda_cache_path, exist_ok=True)
+                intermediate_file = os.path.join(cuda_cache_path, cuda_file_name + '_' + uuid.uuid4().hex + '_tmp' + bin_file_ext)
+                shutil.copyfile(tmp_file, intermediate_file)
+                os.rename(intermediate_file, bin_file) # atomic
+
+        # Load.
+        if verbose:
+            print('Loading... ', end='', flush=True)
+        plugin = tf.load_op_library(bin_file)
+
+        # Add to cache.
+        _plugin_cache[cuda_file] = plugin
+        if verbose:
+            print('Done.', flush=True)
+        return plugin
+
+    except:
+        if verbose:
+            print('Failed!', flush=True)
+        raise
+
+#----------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_all.cu b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_all.cu
new file mode 100644
index 0000000000000000000000000000000000000000..8eefcfbd35d837b9ec595100f57f0bdb6d072349
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_all.cu
@@ -0,0 +1,36 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+// TF-specific helpers.
+
+#define OP_CHECK_CUDA_ERROR(CTX, CUDA_CALL) do { cudaError_t err = CUDA_CALL; OP_REQUIRES(CTX, err == cudaSuccess, errors::Internal("Cuda error: ", cudaGetErrorName(err), "[", #CUDA_CALL, ";]")); } while (0)
+#define OP_CHECK_GL_ERROR(CTX, GL_CALL) do { GL_CALL; GLenum err = glGetError(); OP_REQUIRES(CTX, err == GL_NO_ERROR, errors::Internal("OpenGL error: ", getGLErrorString(err), "[", #GL_CALL, ";]")); } while (0)
+
+// Cuda kernels and CPP all together. What an absolute compilation unit.
+
+#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
+#include "../common/framework.h"
+#include "../common/glutil.cpp"
+
+#include "../common/common.h"
+#include "../common/common.cpp"
+
+#include "../common/rasterize.h"
+#include "../common/rasterize_gl.cpp"
+#include "../common/rasterize.cu"
+#include "tf_rasterize.cu"
+
+#include "../common/interpolate.cu"
+#include "tf_interpolate.cu"
+
+#include "../common/texture.cpp"
+#include "../common/texture.cu"
+#include "tf_texture.cu"
+
+#include "../common/antialias.cu"
+#include "tf_antialias.cu"
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_antialias.cu b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_antialias.cu
new file mode 100644
index 0000000000000000000000000000000000000000..9b14962a8b40e12bfab1ca3a7107d5f5e943a125
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_antialias.cu
@@ -0,0 +1,278 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+// Forward TensorFlow op.
+
+struct AntialiasFwdOp : public OpKernel
+{
+    AntialiasKernelParams m_attribs;
+
+    AntialiasFwdOp(OpKernelConstruction* ctx): OpKernel(ctx)
+    {
+        memset(&m_attribs, 0, sizeof(m_attribs));
+        OP_REQUIRES_OK(ctx, ctx->GetAttr("tri_const", &m_attribs.tri_const));
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        AntialiasKernelParams& p = m_attribs;
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+
+        // Get input.
+        const Tensor& color     = ctx->input(0);
+        const Tensor& rasterOut = ctx->input(1);
+        const Tensor& pos       = ctx->input(2);
+        const Tensor& tri       = ctx->input(3);
+
+        // Instance rendering mode?
+        p.instance_mode = pos.dims() > 2;
+
+        // Extract input dimensions.
+        if (p.instance_mode)
+            p.numVertices = (pos.dims() > 1) ? pos.dim_size(1) : 0;
+        else
+            p.numVertices = (pos.dims() > 0) ? pos.dim_size(0) : 0;
+        p.numTriangles = (tri.dims() > 0) ? tri.dim_size(0) : 0;
+        p.n        = (color.dims() > 0) ? color.dim_size(0) : 0;
+        p.height   = (color.dims() > 1) ? color.dim_size(1) : 0;
+        p.width    = (color.dims() > 2) ? color.dim_size(2) : 0;
+        p.channels = (color.dims() > 3) ? color.dim_size(3) : 0;
+
+        // Sanity checks.
+        OP_REQUIRES(ctx, color.dims() == 4 && color.dim_size(0) > 0 && color.dim_size(1) > 0 && color.dim_size(2) > 0 && color.dim_size(3) > 0, errors::InvalidArgument("color must have shape[>0, >0, >0, >0]"));
+        OP_REQUIRES(ctx, rasterOut.dims() == 4 && rasterOut.dim_size(0) > 0 && rasterOut.dim_size(1) > 0 && rasterOut.dim_size(2) > 0 && rasterOut.dim_size(3) == 4, errors::InvalidArgument("raster_out must have shape[>0, >0, >0, 4]"));
+        OP_REQUIRES(ctx, tri.dims() == 2 && tri.dim_size(0) > 0 && tri.dim_size(1) == 3, errors::InvalidArgument("tri must have shape [>0, 3]"));
+        OP_REQUIRES(ctx, color.dim_size(1) == rasterOut.dim_size(1) && color.dim_size(2) == rasterOut.dim_size(2), errors::InvalidArgument("color and raster_out inputs must have same spatial dimensions"));
+        if (p.instance_mode)
+        {
+            OP_REQUIRES(ctx, pos.dims() == 3 && pos.dim_size(0) > 0 && pos.dim_size(1) > 0 && pos.dim_size(2) == 4, errors::InvalidArgument("pos must have shape [>0, >0, 4] or [>0, 4]"));
+            OP_REQUIRES(ctx, rasterOut.dim_size(0) == p.n && pos.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs color, raster_out, pos"));
+        }
+        else
+        {
+            OP_REQUIRES(ctx, pos.dims() == 2 && pos.dim_size(0) > 0 && pos.dim_size(1) == 4, errors::InvalidArgument("pos must have shape [>0, >0, 4] or [>0, 4]"));
+            OP_REQUIRES(ctx, rasterOut.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs color, raster_out"));
+        }
+
+        // Get input pointers.
+        p.color = color.flat<float>().data();
+        p.rasterOut = rasterOut.flat<float>().data();
+        p.tri = tri.flat<int>().data();
+        p.pos = pos.flat<float>().data();
+
+        // Misc parameters.
+        p.xh = .5f * (float)p.width;
+        p.yh = .5f * (float)p.height;
+
+        // Allocate output tensor.
+        Tensor* outputTensor = NULL;
+        TensorShape outputShape;
+        outputShape.AddDim(p.n);
+        outputShape.AddDim(p.height);
+        outputShape.AddDim(p.width);
+        outputShape.AddDim(p.channels);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(0, outputShape, &outputTensor));
+        p.output = outputTensor->flat<float>().data();
+
+        // Allocate work buffer. One extra int4 for storing counters.
+        Tensor* workTensor = NULL;
+        TensorShape workShape;
+        workShape.AddDim(p.n * p.width * p.height * 8 + 4); // 8 int for a maximum of two work items per pixel.
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(1, workShape, &workTensor));
+        p.workBuffer = (int4*)(workTensor->flat<int>().data());
+
+        // Clear the work counters.
+        OP_CHECK_CUDA_ERROR(ctx, cudaMemsetAsync(p.workBuffer, 0, sizeof(int4), stream));
+
+        // Verify that buffers are aligned to allow float2/float4 operations.
+        OP_REQUIRES(ctx, !((uintptr_t)p.pos        & 15), errors::Internal("pos input tensor not aligned to float4"));
+        OP_REQUIRES(ctx, !((uintptr_t)p.rasterOut  &  7), errors::Internal("raster_out input tensor not aligned to float2"));
+        OP_REQUIRES(ctx, !((uintptr_t)p.workBuffer & 15), errors::Internal("work_buffer internal tensor not aligned to int4"));
+
+        // Kernel parameters.
+        void* args[] = {&p};
+
+        // (Re-)calculate opposite vertex hash.
+        if (!p.evHash || !p.tri_const)
+        {            
+            if (p.allocTriangles < p.numTriangles)
+            {
+                p.allocTriangles = max(p.allocTriangles, 64);
+                while (p.allocTriangles < p.numTriangles)
+                    p.allocTriangles <<= 1; // Must be power of two.
+               
+                // (Re-)allocate memory for the hash.
+                OP_CHECK_CUDA_ERROR(ctx, cudaFree(p.evHash));
+                OP_CHECK_CUDA_ERROR(ctx, cudaMalloc(&p.evHash, p.allocTriangles * AA_HASH_ELEMENTS_PER_TRIANGLE(p.allocTriangles) * sizeof(uint4)));
+                LOG(INFO) << "Increasing topology hash size to accommodate " << p.allocTriangles << " triangles";
+            }
+
+            // Clear the hash and launch the mesh kernel to populate it.
+            OP_CHECK_CUDA_ERROR(ctx, cudaMemsetAsync(p.evHash, 0, p.allocTriangles * AA_HASH_ELEMENTS_PER_TRIANGLE(p.allocTriangles) * sizeof(uint4), stream));
+            OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel((void*)AntialiasFwdMeshKernel, (p.numTriangles - 1) / AA_MESH_KERNEL_THREADS_PER_BLOCK + 1, AA_MESH_KERNEL_THREADS_PER_BLOCK, args, 0, stream));
+        }
+
+        // Copy input to output as a baseline.
+        OP_CHECK_CUDA_ERROR(ctx, cudaMemcpyAsync(p.output, p.color, p.n * p.height * p.width * p.channels * sizeof(float), cudaMemcpyDeviceToDevice, stream));
+
+        // Choose launch parameters for the discontinuity finder kernel and launch.
+        dim3 blockSize(AA_DISCONTINUITY_KERNEL_BLOCK_WIDTH, AA_DISCONTINUITY_KERNEL_BLOCK_HEIGHT, 1);
+        dim3 gridSize = getLaunchGridSize(blockSize, p.width, p.height, p.n);
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel((void*)AntialiasFwdDiscontinuityKernel, gridSize, blockSize, args, 0, stream));
+
+        // Determine optimum block size for the persistent analysis kernel.
+        int device = 0;
+        int numCTA = 0;
+        int numSM  = 0;
+        OP_CHECK_CUDA_ERROR(ctx, cudaGetDevice(&device));
+        OP_CHECK_CUDA_ERROR(ctx, cudaOccupancyMaxActiveBlocksPerMultiprocessor(&numCTA, (void*)AntialiasFwdAnalysisKernel, AA_ANALYSIS_KERNEL_THREADS_PER_BLOCK, 0));
+        OP_CHECK_CUDA_ERROR(ctx, cudaDeviceGetAttribute(&numSM, cudaDevAttrMultiProcessorCount, device));
+
+        // Launch analysis kernel.
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel((void*)AntialiasFwdAnalysisKernel, numCTA * numSM, AA_ANALYSIS_KERNEL_THREADS_PER_BLOCK, args, 0, stream));
+    }
+};
+
+REGISTER_OP("AntialiasFwd")
+    .Input      ("color: float")
+    .Input      ("raster_out: float")
+    .Input      ("pos: float")
+    .Input      ("tri: int32")
+    .Output     ("output: float")
+    .Output     ("work_buffer: int32")
+    .Attr       ("tri_const: int");
+
+REGISTER_KERNEL_BUILDER(Name("AntialiasFwd").Device(DEVICE_GPU), AntialiasFwdOp);
+
+//------------------------------------------------------------------------
+// Gradient TensorFlow op.
+
+struct AntialiasGradOp : public OpKernel
+{
+    AntialiasKernelParams m_attribs;
+
+    AntialiasGradOp(OpKernelConstruction* ctx): OpKernel(ctx)
+    {
+        memset(&m_attribs, 0, sizeof(m_attribs));
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        AntialiasKernelParams& p = m_attribs;
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+
+        // Get input.
+        const Tensor& color      = ctx->input(0);
+        const Tensor& rasterOut  = ctx->input(1);
+        const Tensor& pos        = ctx->input(2);
+        const Tensor& tri        = ctx->input(3);
+        const Tensor& dy         = ctx->input(4);
+        const Tensor& workBuffer = ctx->input(5);
+
+        // Instance rendering mode?
+        p.instance_mode = pos.dims() > 2;
+
+        // Extract input dimensions.
+        if (p.instance_mode)
+            p.numVertices = (pos.dims() > 1) ? pos.dim_size(1) : 0;
+        else
+            p.numVertices = (pos.dims() > 0) ? pos.dim_size(0) : 0;
+        p.numTriangles = (tri.dims() > 0) ? tri.dim_size(0) : 0;
+        p.n        = (color.dims() > 0) ? color.dim_size(0) : 0;
+        p.height   = (color.dims() > 1) ? color.dim_size(1) : 0;
+        p.width    = (color.dims() > 2) ? color.dim_size(2) : 0;
+        p.channels = (color.dims() > 3) ? color.dim_size(3) : 0;
+
+        // Sanity checks.
+        OP_REQUIRES(ctx, dy.dims() == 4 && dy.dim_size(0) > 0 && dy.dim_size(1) > 0 && dy.dim_size(2) > 0 && dy.dim_size(3) > 0, errors::InvalidArgument("dy must have shape[>0, >0, >0, >0]"));
+        OP_REQUIRES(ctx, color.dims() == 4 && color.dim_size(0) > 0 && color.dim_size(1) > 0 && color.dim_size(2) > 0 && color.dim_size(3) > 0, errors::InvalidArgument("color must have shape[>0, >0, >0, >0]"));
+        OP_REQUIRES(ctx, rasterOut.dims() == 4 && rasterOut.dim_size(0) > 0 && rasterOut.dim_size(1) > 0 && rasterOut.dim_size(2) > 0 && rasterOut.dim_size(3) == 4, errors::InvalidArgument("raster_out must have shape[>0, >0, >0, 4]"));
+        OP_REQUIRES(ctx, tri.dims() == 2 && tri.dim_size(0) > 0 && tri.dim_size(1) == 3, errors::InvalidArgument("tri must have shape [>0, 3]"));
+        OP_REQUIRES(ctx, color.dim_size(1) == rasterOut.dim_size(1) && color.dim_size(2) == rasterOut.dim_size(2), errors::InvalidArgument("color and raster_out inputs must have same spatial dimensions"));
+        OP_REQUIRES(ctx, color.dim_size(1) == dy.dim_size(1) && color.dim_size(2) == dy.dim_size(2) && color.dim_size(3) == dy.dim_size(3), errors::InvalidArgument("color and dy inputs must have same dimensions"));
+        if (p.instance_mode)
+        {
+            OP_REQUIRES(ctx, pos.dims() == 3 && pos.dim_size(0) > 0 && pos.dim_size(1) > 0 && pos.dim_size(2) == 4, errors::InvalidArgument("pos must have shape [>0, >0, 4] or [>0, 4]"));
+            OP_REQUIRES(ctx, rasterOut.dim_size(0) == p.n && pos.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs color, raster_out, pos"));
+            OP_REQUIRES(ctx, dy.dim_size(0) == p.n && rasterOut.dim_size(0) == p.n && pos.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs dy, color, raster_out, pos"));
+        }
+        else
+        {
+            OP_REQUIRES(ctx, pos.dims() == 2 && pos.dim_size(0) > 0 && pos.dim_size(1) == 4, errors::InvalidArgument("pos must have shape [>0, >0, 4] or [>0, 4]"));
+            OP_REQUIRES(ctx, rasterOut.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs color, raster_out"));
+            OP_REQUIRES(ctx, dy.dim_size(0) == p.n && rasterOut.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs dy, color, raster_out"));
+        }
+
+        // Get input pointers.
+        p.dy = dy.flat<float>().data();
+        p.color = color.flat<float>().data();
+        p.rasterOut = rasterOut.flat<float>().data();
+        p.tri = tri.flat<int>().data();
+        p.pos = pos.flat<float>().data();
+        p.workBuffer = (int4*)(workBuffer.flat<int>().data());
+
+        // Misc parameters.
+        p.xh = .5f * (float)p.width;
+        p.yh = .5f * (float)p.height;
+
+        // Allocate color gradient output tensor.
+        Tensor* gradColor = NULL;
+        TensorShape gradColorShape;
+        gradColorShape.AddDim(p.n);
+        gradColorShape.AddDim(p.height);
+        gradColorShape.AddDim(p.width);
+        gradColorShape.AddDim(p.channels);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(0, gradColorShape, &gradColor));
+        p.gradColor = gradColor->flat<float>().data();
+
+        // Allocate position gradient output tensor.
+        Tensor* gradPos = NULL;
+        TensorShape gradPosShape;
+        if (p.instance_mode)
+            gradPosShape.AddDim(p.n);
+        gradPosShape.AddDim(p.numVertices);
+        gradPosShape.AddDim(4);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(1, gradPosShape, &gradPos));
+        p.gradPos = gradPos->flat<float>().data();
+
+        // Initialize all the stuff.
+        OP_CHECK_CUDA_ERROR(ctx, cudaMemsetAsync(&p.workBuffer[0].y, 0, sizeof(int), stream)); // Gradient kernel work counter.
+        OP_CHECK_CUDA_ERROR(ctx, cudaMemcpyAsync(p.gradColor, p.dy, p.n * p.height * p.width * p.channels * sizeof(float), cudaMemcpyDeviceToDevice, stream));
+        OP_CHECK_CUDA_ERROR(ctx, cudaMemsetAsync(p.gradPos, 0, (p.instance_mode ? p.n : 1) * p.numVertices * 4 * sizeof(float), stream));
+
+        // Verify that buffers are aligned to allow float2/float4 operations.
+        OP_REQUIRES(ctx, !((uintptr_t)p.pos        & 15), errors::Internal("pos input tensor not aligned to float4"));
+        OP_REQUIRES(ctx, !((uintptr_t)p.workBuffer & 15), errors::Internal("work_buffer internal tensor not aligned to int4"));
+
+        // Launch the gradient kernel.
+        void* args[] = {&p};
+
+        int device = 0;
+        int numCTA = 0;
+        int numSM  = 0;
+        OP_CHECK_CUDA_ERROR(ctx, cudaGetDevice(&device));
+        OP_CHECK_CUDA_ERROR(ctx, cudaOccupancyMaxActiveBlocksPerMultiprocessor(&numCTA, (void*)AntialiasGradKernel, AA_GRAD_KERNEL_THREADS_PER_BLOCK, 0));
+        OP_CHECK_CUDA_ERROR(ctx, cudaDeviceGetAttribute(&numSM, cudaDevAttrMultiProcessorCount, device));
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel((void*)AntialiasGradKernel, numCTA * numSM, AA_GRAD_KERNEL_THREADS_PER_BLOCK, args, 0, stream));
+    }
+};
+
+REGISTER_OP("AntialiasGrad")
+    .Input      ("color: float")
+    .Input      ("raster_out: float")
+    .Input      ("pos: float")
+    .Input      ("tri: int32")
+    .Input      ("dy: float")
+    .Input      ("work_buffer: int32")
+    .Output     ("grad_color: float")
+    .Output     ("grad_pos: float");
+
+REGISTER_KERNEL_BUILDER(Name("AntialiasGrad").Device(DEVICE_GPU), AntialiasGradOp);
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_interpolate.cu b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_interpolate.cu
new file mode 100644
index 0000000000000000000000000000000000000000..612ce1afc5ce41a25496523b193725c1edac64de
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_interpolate.cu
@@ -0,0 +1,301 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+// Common op attribute parser.
+
+static __host__ void interpolateParseOpAttributes(OpKernelConstruction* ctx, InterpolateKernelParams& p, bool enableDA)
+{
+    if (enableDA)
+    {
+        OP_REQUIRES_OK(ctx, ctx->GetAttr("diff_attrs_all", &p.diff_attrs_all));
+        if (!p.diff_attrs_all)
+        {
+            std::vector<int> diff_attrs_vec;
+            OP_REQUIRES_OK(ctx, ctx->GetAttr("diff_attrs", &diff_attrs_vec));
+            OP_REQUIRES(ctx, diff_attrs_vec.size() > 0, errors::InvalidArgument("differentiation enabled with empty diff_attrs list"));
+            OP_REQUIRES(ctx, diff_attrs_vec.size() <= IP_MAX_DIFF_ATTRS, errors::InvalidArgument("too many entries in diff_attrs list (increase IP_MAX_DIFF_ATTRS)"));
+            p.numDiffAttr = diff_attrs_vec.size();
+            memcpy(p.diffAttrs, &diff_attrs_vec[0], diff_attrs_vec.size()*sizeof(int));
+        }
+    }
+}
+
+//------------------------------------------------------------------------
+// Forward TensorFlow op.
+
+template <bool ENABLE_DA>
+struct InterpolateFwdOp : public OpKernel
+{
+    InterpolateKernelParams m_attribs;
+
+    InterpolateFwdOp(OpKernelConstruction* ctx): OpKernel(ctx)
+    {
+        memset(&m_attribs, 0, sizeof(m_attribs));
+        interpolateParseOpAttributes(ctx, m_attribs, ENABLE_DA);
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        InterpolateKernelParams& p = m_attribs;
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+
+        // Get input.
+        const Tensor& attr    = ctx->input(0);
+        const Tensor& rast    = ctx->input(1);
+        const Tensor& tri     = ctx->input(2);
+        const Tensor& rast_db = ctx->input(ENABLE_DA ? 3 : 2);
+
+        // Instance rendering mode?
+        p.instance_mode = attr.dims() > 2;
+
+        // Extract input dimensions.
+        if (p.instance_mode)
+        {
+            p.numVertices  = (attr.dims() > 1) ? attr.dim_size(1) : 0;
+            p.numAttr      = (attr.dims() > 2) ? attr.dim_size(2) : 0;
+        }
+        else
+        {
+            p.numVertices  = (attr.dims() > 0) ? attr.dim_size(0) : 0;
+            p.numAttr      = (attr.dims() > 1) ? attr.dim_size(1) : 0;
+        }
+        p.numTriangles = (tri.dims() > 0) ? tri.dim_size(0) : 0;
+        p.height       = (rast.dims() > 1) ? rast.dim_size(1) : 0;
+        p.width        = (rast.dims() > 2) ? rast.dim_size(2) : 0;
+        p.depth        = (rast.dims() > 0) ? rast.dim_size(0) : 0;
+
+        // Sanity checks.
+        OP_REQUIRES(ctx, rast.dims() == 4 && rast.dim_size(0) > 0 && rast.dim_size(1) > 0 && rast.dim_size(2) > 0 && rast.dim_size(3) == 4, errors::InvalidArgument("rast must have shape[>0, >0, >0, 4]"));
+        OP_REQUIRES(ctx, tri.dims() == 2 && tri.dim_size(0) > 0 && tri.dim_size(1) == 3, errors::InvalidArgument("tri must have shape [>0, 3]"));
+        OP_REQUIRES(ctx, (attr.dims() == 2 || attr.dims() == 3) && attr.dim_size(0) > 0 && attr.dim_size(1) > 0 && (attr.dims() == 2 || attr.dim_size(2) > 0), errors::InvalidArgument("attr must have shape [>0, >0, >0] or [>0, >0]"));
+        if (p.instance_mode)
+            OP_REQUIRES(ctx, attr.dim_size(0) == p.depth || attr.dim_size(0) == 1, errors::InvalidArgument("minibatch size mismatch between inputs rast, attr"));
+        if (ENABLE_DA)
+        {
+            OP_REQUIRES(ctx, rast_db.dims() == 4 && rast_db.dim_size(0) > 0 && rast_db.dim_size(1) > 0 && rast_db.dim_size(2) > 0 && rast_db.dim_size(3) == 4, errors::InvalidArgument("rast_db must have shape[>0, >0, >0, 4]"));
+            OP_REQUIRES(ctx, rast_db.dim_size(1) == rast.dim_size(1) && rast_db.dim_size(2) == rast.dim_size(2), errors::InvalidArgument("spatial size mismatch between inputs rast and rast_db"));
+            OP_REQUIRES(ctx, rast_db.dim_size(0) == p.depth, errors::InvalidArgument("minibatch size mismatch between inputs rast, rast_db"));
+        }
+
+        // All diff attrs mode.
+        if (p.diff_attrs_all)
+            p.numDiffAttr = p.numAttr;
+
+        // Get input pointers.
+        p.attr = attr.flat<float>().data();
+        p.rast = rast.flat<float>().data();
+        p.tri = tri.flat<int>().data();
+        p.attrBC = (p.instance_mode && attr.dim_size(0) == 1) ? 1 : 0;
+        p.rastDB = ENABLE_DA ? rast_db.flat<float>().data() : 0;
+
+        // Allocate main output tensor.
+        Tensor* out_tensor = NULL;
+        TensorShape out_shape;
+        out_shape.AddDim(p.depth);
+        out_shape.AddDim(p.height);
+        out_shape.AddDim(p.width);
+        out_shape.AddDim(p.numAttr);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(0, out_shape, &out_tensor));
+        p.out = out_tensor->flat<float>().data();
+
+        // Allocate pixel differential output tensor.
+        Tensor* out_da_tensor = NULL;
+        out_shape.set_dim(3, p.numDiffAttr * 2);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(1, out_shape, &out_da_tensor));
+        p.outDA = ENABLE_DA ? out_da_tensor->flat<float>().data() : 0;
+
+        // Verify that buffers are aligned to allow float2/float4 operations.
+        OP_REQUIRES(ctx, !((uintptr_t)p.rast   & 15), errors::Internal("rast input tensor not aligned to float4"));
+        OP_REQUIRES(ctx, !((uintptr_t)p.rastDB & 15), errors::Internal("rast_db input tensor not aligned to float4"));        
+        if (ENABLE_DA)
+            OP_REQUIRES(ctx, !((uintptr_t)p.outDA & 7), errors::Internal("out_da output tensor not aligned to float2"));
+
+        // Choose launch parameters.
+        dim3 blockSize = getLaunchBlockSize(IP_FWD_MAX_KERNEL_BLOCK_WIDTH, IP_FWD_MAX_KERNEL_BLOCK_HEIGHT, p.width, p.height);
+        dim3 gridSize  = getLaunchGridSize(blockSize, p.width, p.height, p.depth);
+
+        // Launch CUDA kernel.
+        void* args[] = {&p};
+        void* func = ENABLE_DA ? (void*)InterpolateFwdKernelDa : (void*)InterpolateFwdKernel;
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel(func, gridSize, blockSize, args, 0, stream));
+    }
+};
+
+REGISTER_OP("InterpolateFwd")
+    .Input      ("attr: float")
+    .Input      ("rast: float")
+    .Input      ("tri: int32")
+    .Output     ("out: float")
+    .Output     ("out_da: float");
+
+REGISTER_OP("InterpolateFwdDa")
+    .Input      ("attr: float")
+    .Input      ("rast: float")
+    .Input      ("tri: int32")
+    .Input      ("rast_db: float")
+    .Output     ("out: float")
+    .Output     ("out_da: float")
+    .Attr       ("diff_attrs_all: int")
+    .Attr       ("diff_attrs: list(int)");
+
+REGISTER_KERNEL_BUILDER(Name("InterpolateFwd")  .Device(DEVICE_GPU), InterpolateFwdOp<false>);
+REGISTER_KERNEL_BUILDER(Name("InterpolateFwdDa").Device(DEVICE_GPU), InterpolateFwdOp<true>);
+
+//------------------------------------------------------------------------
+// Gradient TensorFlow op.
+
+template <bool ENABLE_DA>
+struct InterpolateGradOp : public OpKernel
+{
+    InterpolateKernelParams m_attribs;
+
+    InterpolateGradOp(OpKernelConstruction* ctx): OpKernel(ctx)
+    {
+        memset(&m_attribs, 0, sizeof(m_attribs));
+        interpolateParseOpAttributes(ctx, m_attribs, ENABLE_DA);      
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        InterpolateKernelParams& p = m_attribs;
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+
+        // Get input.
+        const Tensor& attr    = ctx->input(0);
+        const Tensor& rast    = ctx->input(1);
+        const Tensor& tri     = ctx->input(2);
+        const Tensor& dy      = ctx->input(3);
+        const Tensor& rast_db = ctx->input(ENABLE_DA ? 4 : 3);
+        const Tensor& dda     = ctx->input(ENABLE_DA ? 5 : 3);
+
+        // Instance rendering mode?
+        p.instance_mode = attr.dims() > 2;
+
+        // Extract input dimensions.
+        if (p.instance_mode)
+        {
+            p.numVertices  = (attr.dims() > 1) ? attr.dim_size(1) : 0;
+            p.numAttr      = (attr.dims() > 2) ? attr.dim_size(2) : 0;
+        }
+        else
+        {
+            p.numVertices  = (attr.dims() > 0) ? attr.dim_size(0) : 0;
+            p.numAttr      = (attr.dims() > 1) ? attr.dim_size(1) : 0;
+        }
+        p.numTriangles = (tri.dims() > 0) ? tri.dim_size(0) : 0;
+        p.depth        = (rast.dims() > 0) ? rast.dim_size(0) : 0;
+        p.height       = (rast.dims() > 1) ? rast.dim_size(1) : 0;
+        p.width        = (rast.dims() > 2) ? rast.dim_size(2) : 0;
+        int attr_depth = p.instance_mode ? (attr.dims() > 1 ? attr.dim_size(0) : 0) : 1;
+
+        // Sanity checks.
+        OP_REQUIRES(ctx, rast.dims() == 4 && rast.dim_size(0) > 0 && rast.dim_size(1) > 0 && rast.dim_size(2) > 0 && rast.dim_size(3) == 4, errors::InvalidArgument("rast must have shape[>0, >0, >0, 4]"));
+        OP_REQUIRES(ctx, tri.dims() == 2 && tri.dim_size(0) > 0 && tri.dim_size(1) == 3, errors::InvalidArgument("tri must have shape [>0, 3]"));
+        OP_REQUIRES(ctx, (attr.dims() == 2 || attr.dims() == 3) && attr.dim_size(0) > 0 && attr.dim_size(1) > 0 && (attr.dims() == 2 || attr.dim_size(2) > 0), errors::InvalidArgument("attr must have shape [>0, >0, >0] or [>0, >0]"));
+        OP_REQUIRES(ctx, dy.dims() == 4 && dy.dim_size(0) > 0 && dy.dim_size(1) == p.height && dy.dim_size(2) == p.width && dy.dim_size(3) > 0, errors::InvalidArgument("dy must have shape [>0, height, width, >0]"));
+        OP_REQUIRES(ctx, dy.dim_size(3) == p.numAttr, errors::InvalidArgument("argument count mismatch between inputs dy, attr"));
+        OP_REQUIRES(ctx, (attr_depth == p.depth || attr_depth == 1) && dy.dim_size(0) == p.depth, errors::InvalidArgument("minibatch size mismatch between inputs rast, dy, attr"));
+        if (ENABLE_DA)
+        {
+            OP_REQUIRES(ctx, dda.dims() == 4 && dda.dim_size(0) > 0 && dda.dim_size(1) == p.height && dda.dim_size(2) == p.width, errors::InvalidArgument("dda must have shape [>0, height, width, ?]"));
+            OP_REQUIRES(ctx, dda.dim_size(0) == p.depth, errors::InvalidArgument("minibatch size mismatch between rast, dda"));
+        }
+
+        // All diff attrs mode.
+        if (p.diff_attrs_all)
+            p.numDiffAttr = p.numAttr;
+
+        // Get input pointers.
+        p.attr   = attr.flat<float>().data();
+        p.rast   = rast.flat<float>().data();
+        p.tri    = tri.flat<int>().data();
+        p.dy     = dy.flat<float>().data();
+        p.rastDB = ENABLE_DA ? rast_db.flat<float>().data() : 0;
+        p.dda    = ENABLE_DA ? dda.flat<float>().data() : 0;
+        p.attrBC = (p.instance_mode && attr_depth < p.depth) ? 1 : 0;
+
+        // Allocate attribute gradient output tensor.
+        Tensor* grad_attr_tensor = NULL;
+        TensorShape grad_attr_shape;
+        if (p.instance_mode)
+            grad_attr_shape.AddDim(attr_depth);
+        grad_attr_shape.AddDim(p.numVertices);
+        grad_attr_shape.AddDim(p.numAttr);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(0, grad_attr_shape, &grad_attr_tensor));
+        p.gradAttr = grad_attr_tensor->flat<float>().data();
+
+        // Allocate bary gradient output tensor.
+        Tensor* grad_rast_tensor = NULL;
+        TensorShape grad_rast_shape;
+        grad_rast_shape.AddDim(p.depth);
+        grad_rast_shape.AddDim(p.height);
+        grad_rast_shape.AddDim(p.width);
+        grad_rast_shape.AddDim(4);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(1, grad_rast_shape, &grad_rast_tensor));
+        p.gradRaster = grad_rast_tensor->flat<float>().data();
+
+        // Allocate bary pixel diff gradient output tensor.
+        if (ENABLE_DA)
+        {
+            Tensor* grad_rast_db_tensor = NULL;
+            OP_REQUIRES_OK(ctx, ctx->allocate_output(2, grad_rast_shape, &grad_rast_db_tensor));
+            p.gradRasterDB = grad_rast_db_tensor->flat<float>().data();
+        }
+        
+        // Clear attribute gradients.
+        cudaMemsetAsync(p.gradAttr, 0, attr_depth * p.numVertices * p.numAttr * sizeof(float), stream);
+
+        // Verify that buffers are aligned to allow float2/float4 operations.
+        OP_REQUIRES(ctx, !((uintptr_t)p.rast   & 15), errors::Internal("rast input tensor not aligned to float4"));
+        OP_REQUIRES(ctx, !((uintptr_t)p.gradRaster & 15), errors::Internal("grad_rast output tensor not aligned to float4"));
+        if (ENABLE_DA)
+        {
+            OP_REQUIRES(ctx, !((uintptr_t)p.dda & 7), errors::Internal("dda input tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.rastDB & 15), errors::Internal("rast_db input tensor not aligned to float4"));        
+            OP_REQUIRES(ctx, !((uintptr_t)p.gradRasterDB & 15), errors::Internal("grad_rast_db output tensor not aligned to float4"));
+        }
+    
+        // Choose launch parameters.
+        dim3 blockSize = getLaunchBlockSize(IP_GRAD_MAX_KERNEL_BLOCK_WIDTH, IP_GRAD_MAX_KERNEL_BLOCK_HEIGHT, p.width, p.height);
+        dim3 gridSize  = getLaunchGridSize(blockSize, p.width, p.height, p.depth);
+
+        // Launch CUDA kernel.
+        void* args[] = {&p};
+        void* func = ENABLE_DA ? (void*)InterpolateGradKernelDa : (void*)InterpolateGradKernel;
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel(func, gridSize, blockSize, args, 0, stream));
+    }
+};
+
+REGISTER_OP("InterpolateGrad")
+    .Input      ("attr: float")
+    .Input      ("rast: float")
+    .Input      ("tri: int32")
+    .Input      ("dy: float")
+    .Output     ("grad_attr: float")
+    .Output     ("grad_rast: float")
+    ;
+
+REGISTER_OP("InterpolateGradDa")
+    .Input      ("attr: float")
+    .Input      ("rast: float")
+    .Input      ("tri: int32")
+    .Input      ("dy: float")
+    .Input      ("rast_db: float")
+    .Input      ("dda: float")
+    .Output     ("grad_attr: float")
+    .Output     ("grad_rast: float")
+    .Output     ("grad_rast_db: float")
+    .Attr       ("diff_attrs_all: int")
+    .Attr       ("diff_attrs: list(int)");
+    ;
+
+REGISTER_KERNEL_BUILDER(Name("InterpolateGrad")  .Device(DEVICE_GPU), InterpolateGradOp<false>);
+REGISTER_KERNEL_BUILDER(Name("InterpolateGradDa").Device(DEVICE_GPU), InterpolateGradOp<true>);
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_rasterize.cu b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_rasterize.cu
new file mode 100644
index 0000000000000000000000000000000000000000..4d0a2616d3b74a4d0e76ccfefb6552d4a7f2a65f
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_rasterize.cu
@@ -0,0 +1,242 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+// Forward TensorFlow op.
+
+struct RasterizeFwdOp : public OpKernel
+{
+    RasterizeGLState        m_glState;              // OpenGL-related persistent state.
+    int                     m_tri_const;            // 1 if triangle array is known to be constant.
+
+    RasterizeFwdOp(OpKernelConstruction* ctx):
+        OpKernel(ctx)
+    {
+        memset(&m_glState, 0, sizeof(RasterizeGLState));
+        OP_REQUIRES_OK(ctx, ctx->GetAttr("enable_db", &m_glState.enableDB));
+        OP_REQUIRES_OK(ctx, ctx->GetAttr("tri_const", &m_tri_const));
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+
+        // Check that input shapes are correct.
+        const Tensor& pos = ctx->input(0);
+        const Tensor& tri = ctx->input(1);
+        const Tensor& resolution = ctx->input(2);
+        const Tensor& ranges = ctx->input(3);
+
+        // Determine number of outputs
+        int num_outputs = m_glState.enableDB ? 2 : 1;
+
+        // Determine instance mode and check input dimensions.
+        bool instance_mode = pos.dims() > 2;
+        if (instance_mode)
+        {
+            OP_REQUIRES(ctx, pos.dims() == 3 && pos.dim_size(0) > 0 && pos.dim_size(1) > 0 && pos.dim_size(2) == 4, errors::InvalidArgument("instance mode - pos must have shape [>0, >0, 4]"));
+            OP_REQUIRES(ctx, tri.dims() == 2 && tri.dim_size(0) > 0 && tri.dim_size(1) == 3, errors::InvalidArgument("tri must have shape [>0, 3]"));
+            OP_REQUIRES(ctx, resolution.dims() == 1 && resolution.dim_size(0) == 2, errors::InvalidArgument("resolution must have shape [2]"));
+        }
+        else
+        {
+            OP_REQUIRES(ctx, pos.dims() == 2 && pos.dim_size(0) > 0 && pos.dim_size(1) == 4, errors::InvalidArgument("range mode - pos must have shape [>0, 4]"));
+            OP_REQUIRES(ctx, tri.dims() == 2 && tri.dim_size(0) > 0 && tri.dim_size(1) == 3, errors::InvalidArgument("tri must have shape [>0, 3]"));
+            OP_REQUIRES(ctx, resolution.dims() == 1 && resolution.dim_size(0) == 2, errors::InvalidArgument("resolution must have shape [2]"));
+            OP_REQUIRES(ctx, ranges.dims() == 2 && ranges.dim_size(0) > 0 && ranges.dim_size(1) == 2, errors::InvalidArgument("range mode - ranges must have shape [>0, 2]"));
+        }
+
+        // Get output shape.
+        const int32_t* res_in = resolution.flat<int32_t>().data(); // This is in CPU memory.
+        int height = res_in[0];
+        int width  = res_in[1];
+        int depth  = instance_mode ? pos.dim_size(0) : ranges.dim_size(0);
+        OP_REQUIRES(ctx, height > 0 && width > 0, errors::InvalidArgument("resolution must be [>0, >0]"));
+
+        // Get position and triangle buffer sizes in int32/float32.
+        int posCount = 4 * pos.dim_size(0) * (instance_mode ? pos.dim_size(1) : 1);
+        int triCount = 3 * tri.dim_size(0);
+
+        // Init context and GL?
+        bool initCtx = !m_glState.glFBO;
+        if (initCtx)
+        {
+            const DeviceBase::GpuDeviceInfo* g = ctx->device()->tensorflow_gpu_device_info();
+            int cudaDeviceIdx = g ? g->gpu_id : -1;
+            rasterizeInitGLContext(ctx, m_glState, cudaDeviceIdx); // In common/rasterize.cpp
+        }
+        else
+            setGLContext(m_glState.glctx); // (Re-)Activate GL context.
+
+        // Resize all buffers.
+        bool changes = false;
+        rasterizeResizeBuffers(ctx, m_glState, changes, posCount, triCount, width, height, depth); // In common/rasterize_gl.cpp
+        if (changes)
+        {
+#ifdef _WIN32
+            // Workaround for occasional blank first frame on Windows.
+            releaseGLContext();
+            setGLContext(m_glState.glctx);
+#endif
+        }
+
+        // Copy input data to GL and render.
+        const float* posPtr = pos.flat<float>().data();
+        const int32_t* rangesPtr = instance_mode ? 0 : ranges.flat<int32_t>().data(); // This is in CPU memory.
+        const int32_t* triPtr = (initCtx || !m_tri_const) ? tri.flat<int32_t>().data() : NULL; // Copy triangles only if needed.
+        int vtxPerInstance = instance_mode ? pos.dim_size(1) : 0;
+        rasterizeRender(ctx, m_glState, stream, posPtr, posCount, vtxPerInstance, triPtr, triCount, rangesPtr, width, height, depth, -1);
+
+        // Allocate output tensors.
+        TensorShape output_shape;
+        output_shape.AddDim(depth);
+        output_shape.AddDim(height);
+        output_shape.AddDim(width);
+        output_shape.AddDim(4);
+        float* outputPtr[2];
+        for (int i=0; i < 2; i++)
+        {
+            if (i >= num_outputs)
+                output_shape.set_dim(3, 0); // Zero channels for unwanted out_db tensor.
+            Tensor* output_tensor = NULL;
+            OP_REQUIRES_OK(ctx, ctx->allocate_output(i, output_shape, &output_tensor));
+            if (i < num_outputs)
+                outputPtr[i] = output_tensor->flat<float>().data();
+        }
+
+        // Copy rasterized results into CUDA buffers.
+        rasterizeCopyResults(ctx, m_glState, stream, outputPtr, width, height, depth);
+
+        // Done. Release GL context.
+        releaseGLContext();
+    }
+};
+
+REGISTER_OP("RasterizeFwd")
+    .Input      ("pos: float")
+    .Input      ("tri: int32")
+    .Input      ("resolution: int32")
+    .Input      ("ranges: int32")
+    .Output     ("out: float")
+    .Output     ("out_db: float")
+    .Attr       ("enable_db: int")
+    .Attr       ("tri_const: int");
+
+REGISTER_KERNEL_BUILDER(Name("RasterizeFwd").Device(DEVICE_GPU).HostMemory("resolution").HostMemory("ranges"), RasterizeFwdOp);
+
+//------------------------------------------------------------------------
+// Gradient TensorFlow op.
+
+template <bool ENABLE_DB>
+struct RasterizeGradOp : public OpKernel
+{
+    RasterizeGradParams m_attribs;
+
+    RasterizeGradOp(OpKernelConstruction* ctx): OpKernel(ctx)
+    {
+        memset(&m_attribs, 0, sizeof(m_attribs));
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        RasterizeGradParams& p = m_attribs;
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+
+        // Input tensors.
+        const Tensor& pos = ctx->input(0);
+        const Tensor& tri = ctx->input(1);
+        const Tensor& out = ctx->input(2);
+        const Tensor& dy  = ctx->input(3);
+        const Tensor& ddb = ctx->input(ENABLE_DB ? 4 : 3);
+
+        // Determine instance mode.
+        p.instance_mode = (pos.dims() > 2) ? 1 : 0;
+
+        // Shape is taken from the rasterizer output tensor.
+        OP_REQUIRES(ctx, out.dims() == 4, errors::InvalidArgument("out must be rank-4"));
+        p.depth  = out.dim_size(0);
+        p.height = out.dim_size(1);
+        p.width  = out.dim_size(2);
+        OP_REQUIRES(ctx, p.depth > 0 && p.height > 0 && p.width > 0, errors::InvalidArgument("resolution must be [>0, >0, >0]"));
+
+        // Check other shapes.
+        if (p.instance_mode)
+            OP_REQUIRES(ctx, pos.dims() == 3 && pos.dim_size(0) == p.depth && pos.dim_size(1) > 0 && pos.dim_size(2) == 4, errors::InvalidArgument("pos must have shape [depth, >0, 4]"));
+        else
+            OP_REQUIRES(ctx, pos.dims() == 2 && pos.dim_size(0) > 0 && pos.dim_size(1) == 4, errors::InvalidArgument("pos must have shape [>0, 4]"));
+        OP_REQUIRES(ctx, tri.dims() == 2 && tri.dim_size(0) > 0 && tri.dim_size(1) == 3, errors::InvalidArgument("tri must have shape [>0, 3]"));
+        OP_REQUIRES(ctx, out.dims() == 4 && out.dim_size(0) == p.depth && out.dim_size(1) == p.height && out.dim_size(2) == p.width && out.dim_size(3) == 4, errors::InvalidArgument("out must have shape [depth, height, width, 4]"));
+        OP_REQUIRES(ctx,  dy.dims() == 4 &&  dy.dim_size(0) == p.depth &&  dy.dim_size(1) == p.height &&  dy.dim_size(2) == p.width &&  dy.dim_size(3) == 4, errors::InvalidArgument("dy must have shape [depth, height, width, 4]"));
+        if (ENABLE_DB)
+            OP_REQUIRES(ctx, ddb.dims() == 4 && ddb.dim_size(0) == p.depth && ddb.dim_size(1) == p.height && ddb.dim_size(2) == p.width && ddb.dim_size(3) == 4, errors::InvalidArgument("ddb must have shape [depth, height, width, 4]"));
+
+        // Populate parameters.
+        p.numTriangles = tri.dim_size(0);
+        p.numVertices = p.instance_mode ? pos.dim_size(1) : pos.dim_size(0);
+        p.pos = pos.flat<float>().data();
+        p.tri = tri.flat<int>().data();
+        p.out = out.flat<float>().data();
+        p.dy  = dy.flat<float>().data();
+        p.ddb = ENABLE_DB ? ddb.flat<float>().data() : 0;
+
+        // Set up pixel position to clip space x, y transform.
+        p.xs = 2.f / (float)p.width;
+        p.xo = 1.f / (float)p.width - 1.f;
+        p.ys = 2.f / (float)p.height;
+        p.yo = 1.f / (float)p.height - 1.f;
+
+        // Allocate output tensor for position gradients.
+        Tensor* grad_tensor = NULL;
+        TensorShape grad_shape;
+        if (p.instance_mode)
+            grad_shape.AddDim(p.depth);
+        grad_shape.AddDim(p.numVertices);
+        grad_shape.AddDim(4);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(0, grad_shape, &grad_tensor));
+        p.grad = grad_tensor->flat<float>().data();
+
+        // Clear the output buffers.
+        size_t gradBytes = (p.instance_mode ? p.depth : 1) * p.numVertices * 4 * sizeof(float);
+        cudaMemsetAsync(p.grad, 0, gradBytes, stream);
+
+        // Verify that buffers are aligned to allow float2/float4 operations.
+        OP_REQUIRES(ctx, !((uintptr_t)p.pos & 15), errors::Internal("pos input tensor not aligned to float4"));
+        OP_REQUIRES(ctx, !((uintptr_t)p.dy  &  7), errors::Internal("dy input tensor not aligned to float2"));
+        if (ENABLE_DB)
+            OP_REQUIRES(ctx, !((uintptr_t)p.ddb & 15), errors::Internal("ddb input tensor not aligned to float4"));
+
+        // Choose launch parameters.
+        dim3 blockSize = getLaunchBlockSize(RAST_GRAD_MAX_KERNEL_BLOCK_WIDTH, RAST_GRAD_MAX_KERNEL_BLOCK_HEIGHT, p.width, p.height);
+        dim3 gridSize  = getLaunchGridSize(blockSize, p.width, p.height, p.depth);
+
+        // Launch CUDA kernel.
+        void* args[] = {&p};
+        void* func = ENABLE_DB ? (void*)RasterizeGradKernelDb : (void*)RasterizeGradKernel;
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel(func, gridSize, blockSize, args, 0, stream));
+    }
+};
+
+REGISTER_OP("RasterizeGrad")
+    .Input      ("pos: float")
+    .Input      ("tri: int32")
+    .Input      ("out: float")
+    .Input      ("dy: float")
+    .Output     ("grad: float");
+
+REGISTER_OP("RasterizeGradDb")
+    .Input      ("pos: float")
+    .Input      ("tri: int32")
+    .Input      ("out: float")
+    .Input      ("dy: float")
+    .Input      ("ddb: float")
+    .Output     ("grad: float");
+
+REGISTER_KERNEL_BUILDER(Name("RasterizeGrad")  .Device(DEVICE_GPU), RasterizeGradOp<false>);
+REGISTER_KERNEL_BUILDER(Name("RasterizeGradDb").Device(DEVICE_GPU), RasterizeGradOp<true>);
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_texture.cu b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_texture.cu
new file mode 100644
index 0000000000000000000000000000000000000000..c5382fed28236da09d20a04c0524a937383daf5a
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/tensorflow/tf_texture.cu
@@ -0,0 +1,525 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+//------------------------------------------------------------------------
+// Common op attribute parser.
+
+static __host__ void parseOpAttributes(OpKernelConstruction* ctx, TextureKernelParams& p)
+{
+    // Mip and filter modes.
+    OP_REQUIRES_OK(ctx, ctx->GetAttr("filter_mode", &p.filterMode));
+    OP_REQUIRES(ctx, p.filterMode >= 0 && p.filterMode < TEX_MODE_COUNT, errors::InvalidArgument("filter_mode unsupported"));
+    p.enableMip = (p.filterMode == TEX_MODE_LINEAR_MIPMAP_NEAREST || p.filterMode == TEX_MODE_LINEAR_MIPMAP_LINEAR);
+
+    // Mip level clamp.
+    if (p.enableMip)
+    {
+        OP_REQUIRES_OK(ctx, ctx->GetAttr("max_mip_level", &p.mipLevelLimit));
+        OP_REQUIRES(ctx, p.mipLevelLimit >= -1, errors::InvalidArgument("invalid max_mip_level"));
+        ctx->GetAttr("tex_const", &p.texConst); // Only available in forward op.
+    }
+
+    // Boundary mode.
+    OP_REQUIRES_OK(ctx, ctx->GetAttr("boundary_mode", &p.boundaryMode));
+    OP_REQUIRES(ctx, p.boundaryMode >= 0 && p.boundaryMode < TEX_BOUNDARY_MODE_COUNT, errors::InvalidArgument("boundary_mode unsupported"));
+}
+
+//------------------------------------------------------------------------
+// Forward TensorFlow op.
+
+struct TextureFwdOp : public OpKernel
+{
+    TextureKernelParams m_attribs;
+    PersistentTensor    m_persistentMipTensor; // Used if texture is constant and mips are enabled.
+    bool                m_persistentMipTensorInitialized;
+
+    TextureFwdOp(OpKernelConstruction* ctx): OpKernel(ctx)
+    {
+        memset(&m_attribs, 0, sizeof(m_attribs));
+        m_persistentMipTensorInitialized = false;
+        parseOpAttributes(ctx, m_attribs);
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        TextureKernelParams& p = m_attribs;
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+        bool cube_mode = (p.boundaryMode == TEX_BOUNDARY_MODE_CUBE);
+
+        // Get input.
+        const Tensor& tex   = ctx->input(0);
+        const Tensor& uv    = ctx->input(1);
+        const Tensor& uv_da = ctx->input(p.enableMip ? 2 : 1);
+
+        // Extract input dimensions.
+        p.n         = (uv.dims() > 0) ? uv.dim_size(0) : 0;
+        p.imgHeight = (uv.dims() > 1) ? uv.dim_size(1) : 0;
+        p.imgWidth  = (uv.dims() > 2) ? uv.dim_size(2) : 0;
+        p.texDepth  = (tex.dims() > 0) ? tex.dim_size(0) : 0;
+        if (!cube_mode)
+        {
+            p.texHeight = (tex.dims() > 1) ? tex.dim_size(1) : 0;
+            p.texWidth  = (tex.dims() > 2) ? tex.dim_size(2) : 0;
+            p.channels  = (tex.dims() > 3) ? tex.dim_size(3) : 0;
+        }
+        else
+        {
+            p.texHeight = (tex.dims() > 2) ? tex.dim_size(2) : 0;
+            p.texWidth  = (tex.dims() > 3) ? tex.dim_size(3) : 0;
+            p.channels  = (tex.dims() > 4) ? tex.dim_size(4) : 0;
+        }
+
+        // Sanity checks.
+        if (!cube_mode)
+        {
+            OP_REQUIRES(ctx, tex.dims() == 4 && tex.dim_size(0) > 0 && tex.dim_size(1) > 0 && tex.dim_size(2) > 0 && tex.dim_size(3) > 0, errors::InvalidArgument("tex must have shape[>0, >0, >0, >0]"));
+            OP_REQUIRES(ctx, uv.dims() == 4 && uv.dim_size(0) > 0 && uv.dim_size(1) > 0 && uv.dim_size(2) > 0 && uv.dim_size(3) == 2, errors::InvalidArgument("uv must have shape [>0, >0, >0, 2]"));
+        }
+        else
+        {
+            OP_REQUIRES(ctx, tex.dims() == 5 && tex.dim_size(0) > 0 && tex.dim_size(1) == 6 && tex.dim_size(2) > 0 && tex.dim_size(3) > 0 && tex.dim_size(4) > 0, errors::InvalidArgument("tex must have shape[>0, 6, >0, >0, >0] in cube map mode"));
+            OP_REQUIRES(ctx, uv.dims() == 4 && uv.dim_size(0) > 0 && uv.dim_size(1) > 0 && uv.dim_size(2) > 0 && uv.dim_size(3) == 3, errors::InvalidArgument("uv must have shape [>0, >0, >0, 3] in cube map mode"));
+            OP_REQUIRES(ctx, tex.dim_size(2) == tex.dim_size(3), errors::InvalidArgument("texture shape must be square in cube map mode"));
+        }
+        OP_REQUIRES(ctx, tex.dim_size(0) == 1 || tex.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs tex, uv"));
+        OP_REQUIRES(ctx, p.texWidth <= (1 << TEX_MAX_MIP_LEVEL) && p.texHeight <= (1 << TEX_MAX_MIP_LEVEL), errors::InvalidArgument("texture size too large"));
+        if (p.enableMip)
+        {
+            if (!cube_mode)
+                OP_REQUIRES(ctx, uv_da.dims() == 4 && uv_da.dim_size(0) == p.n && uv_da.dim_size(1) == p.imgHeight && uv_da.dim_size(2) == p.imgWidth && uv_da.dim_size(3) == 4, errors::InvalidArgument("uv_da must have shape [minibatch_size, height, width, 4]"));
+            else
+                OP_REQUIRES(ctx, uv_da.dims() == 4 && uv_da.dim_size(0) == p.n && uv_da.dim_size(1) == p.imgHeight && uv_da.dim_size(2) == p.imgWidth && uv_da.dim_size(3) == 6, errors::InvalidArgument("uv_da must have shape [minibatch_size, height, width, 6] in cube map mode"));
+        }
+
+        // Get input pointers.
+        p.tex[0] = tex.flat<float>().data();
+        p.uv = uv.flat<float>().data();
+        p.uvDA = p.enableMip ? uv_da.flat<float>().data() : 0;
+
+        // Allocate output tensor.
+        Tensor* out_tensor = NULL;
+        TensorShape out_shape;
+        out_shape.AddDim(p.n);
+        out_shape.AddDim(p.imgHeight);
+        out_shape.AddDim(p.imgWidth);
+        out_shape.AddDim(p.channels);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(0, out_shape, &out_tensor));
+        p.out = out_tensor->flat<float>().data();
+
+        // Choose kernel variants based on channel count.
+        void* args[] = {&p};
+        int channel_div_idx = 0;
+        if (!(p.channels & 3))
+            channel_div_idx = 2;  // Channel count divisible by 4.
+        else if (!(p.channels & 1))
+            channel_div_idx = 1;  // Channel count divisible by 2.
+
+        // Mip-related setup.
+        float* pmip = 0;
+        if (p.enableMip)
+        {
+            // Generate mip offsets.
+            int mipOffsets[TEX_MAX_MIP_LEVEL];
+            int mipTotal = calculateMipInfo(ctx, p, mipOffsets);
+
+            // Mip output tensor.
+            Tensor* mip_tensor = NULL;
+            TensorShape mip_shape;
+            mip_shape.AddDim(mipTotal);
+
+            // If texture is constant, calculate mip stack only once.
+            bool computeMip = true;
+            if (p.texConst)
+            {
+                // First execution?
+                if (!m_persistentMipTensorInitialized)
+                {
+                    // Allocate a persistent mip tensor.
+                    OP_REQUIRES_OK(ctx, ctx->allocate_persistent(DT_FLOAT, mip_shape, &m_persistentMipTensor, &mip_tensor));
+                    m_persistentMipTensorInitialized = true;
+                }
+                else
+                {
+                    // Reuse the persistent tensor, do not recompute mip levels.
+                    mip_tensor = m_persistentMipTensor.AccessTensor(ctx);
+                    computeMip = false;
+                }
+
+                // Set as output tensor as well.
+                ctx->set_output(1, *mip_tensor);
+            }
+            else
+            {
+                // Allocate an output tensor as usual.
+                OP_REQUIRES_OK(ctx, ctx->allocate_output(1, mip_shape, &mip_tensor));
+            }
+
+            pmip = mip_tensor->flat<float>().data(); // Pointer to data.
+            for (int i=1; i <= p.mipLevelMax; i++)
+                p.tex[i] = pmip + mipOffsets[i]; // Pointers to mip levels.
+
+            // Build mip levels if needed.
+            if (computeMip)
+            {
+                for (int i=1; i <= p.mipLevelMax; i++)
+                {
+                    int2 ms = mipLevelSize(p, i);
+                    int3 sz = make_int3(ms.x, ms.y, p.texDepth);
+                    dim3 blockSize = getLaunchBlockSize(TEX_FWD_MAX_MIP_KERNEL_BLOCK_WIDTH, TEX_FWD_MAX_MIP_KERNEL_BLOCK_HEIGHT, sz.x, sz.y);
+                    dim3 gridSize  = getLaunchGridSize(blockSize, sz.x, sz.y, sz.z * (cube_mode ? 6 : 1));
+                    p.mipLevelOut = i;
+
+                    void* build_func_tbl[3] = { (void*)MipBuildKernel1, (void*)MipBuildKernel2, (void*)MipBuildKernel4 };
+                    OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel(build_func_tbl[channel_div_idx], gridSize, blockSize, args, 0, stream));
+                }
+            }
+        }
+
+        // Verify that buffers are aligned to allow float2/float4 operations. Unused pointers are zero so always aligned.
+        if (!cube_mode)
+            OP_REQUIRES(ctx, !((uintptr_t)p.uv & 7), errors::Internal("uv input tensor not aligned to float2"));
+        if ((p.channels & 3) == 0)
+        {
+            OP_REQUIRES(ctx, !((uintptr_t)p.tex[0] & 15), errors::Internal("tex input tensor not aligned to float4"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.out    & 15), errors::Internal("out output tensor not aligned to float4"));
+            OP_REQUIRES(ctx, !((uintptr_t)pmip     & 15), errors::Internal("mip output tensor not aligned to float4"));
+        }
+        if ((p.channels & 1) == 0)
+        {
+            OP_REQUIRES(ctx, !((uintptr_t)p.tex[0] & 7), errors::Internal("tex input tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.out    & 7), errors::Internal("out output tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)pmip     & 7), errors::Internal("mip output tensor not aligned to float2"));
+        }
+        if (!cube_mode)
+            OP_REQUIRES(ctx, !((uintptr_t)p.uvDA & 15), errors::Internal("uv_da input tensor not aligned to float4"));
+        else
+            OP_REQUIRES(ctx, !((uintptr_t)p.uvDA & 7), errors::Internal("uv_da input tensor not aligned to float2"));
+
+        // Choose launch parameters for texture lookup kernel.
+        dim3 blockSize = getLaunchBlockSize(TEX_FWD_MAX_KERNEL_BLOCK_WIDTH, TEX_FWD_MAX_KERNEL_BLOCK_HEIGHT, p.imgWidth, p.imgHeight);
+        dim3 gridSize  = getLaunchGridSize(blockSize, p.imgWidth, p.imgHeight, p.n);
+
+        // Choose kernel based on filter mode, cube mode, and datatype.
+        void* func_tbl[TEX_MODE_COUNT * 3 * 2] = {
+            (void*)TextureFwdKernelNearest1,
+            (void*)TextureFwdKernelNearest2,
+            (void*)TextureFwdKernelNearest4,
+            (void*)TextureFwdKernelLinear1,
+            (void*)TextureFwdKernelLinear2,
+            (void*)TextureFwdKernelLinear4,
+            (void*)TextureFwdKernelLinearMipmapNearest1,
+            (void*)TextureFwdKernelLinearMipmapNearest2,
+            (void*)TextureFwdKernelLinearMipmapNearest4,
+            (void*)TextureFwdKernelLinearMipmapLinear1,
+            (void*)TextureFwdKernelLinearMipmapLinear2,
+            (void*)TextureFwdKernelLinearMipmapLinear4,
+            (void*)TextureFwdKernelCubeNearest1,
+            (void*)TextureFwdKernelCubeNearest2,
+            (void*)TextureFwdKernelCubeNearest4,
+            (void*)TextureFwdKernelCubeLinear1,
+            (void*)TextureFwdKernelCubeLinear2,
+            (void*)TextureFwdKernelCubeLinear4,
+            (void*)TextureFwdKernelCubeLinearMipmapNearest1,
+            (void*)TextureFwdKernelCubeLinearMipmapNearest2,
+            (void*)TextureFwdKernelCubeLinearMipmapNearest4,
+            (void*)TextureFwdKernelCubeLinearMipmapLinear1,
+            (void*)TextureFwdKernelCubeLinearMipmapLinear2,
+            (void*)TextureFwdKernelCubeLinearMipmapLinear4,
+        };
+
+        // Function index.
+        int func_idx = p.filterMode;
+        if (cube_mode)
+            func_idx += TEX_MODE_COUNT;
+        func_idx = func_idx * 3 + channel_div_idx;
+
+        // Launch kernel.
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel(func_tbl[func_idx], gridSize, blockSize, args, 0, stream));
+    }
+};
+
+REGISTER_OP("TextureFwd")
+    .Input      ("tex: float")
+    .Input      ("uv: float")
+    .Output     ("out: float")
+    .Attr       ("filter_mode: int")
+    .Attr       ("boundary_mode: int");
+
+REGISTER_OP("TextureFwdMip")
+    .Input      ("tex: float")
+    .Input      ("uv: float")
+    .Input      ("uv_da: float")
+    .Output     ("out: float")
+    .Output     ("mip: float")
+    .Attr       ("filter_mode: int")
+    .Attr       ("boundary_mode: int")
+    .Attr       ("tex_const: int")
+    .Attr       ("max_mip_level: int");
+
+REGISTER_KERNEL_BUILDER(Name("TextureFwd")   .Device(DEVICE_GPU), TextureFwdOp);
+REGISTER_KERNEL_BUILDER(Name("TextureFwdMip").Device(DEVICE_GPU), TextureFwdOp);
+
+//------------------------------------------------------------------------
+// Gradient TensorFlow op.
+
+struct TextureGradOp : public OpKernel
+{
+    TextureKernelParams m_attribs;
+
+    TextureGradOp(OpKernelConstruction* ctx): OpKernel(ctx)
+    {
+        memset(&m_attribs, 0, sizeof(m_attribs));
+        parseOpAttributes(ctx, m_attribs);
+    }
+
+    void Compute(OpKernelContext* ctx)
+    {
+        TextureKernelParams& p = m_attribs;
+        cudaStream_t stream = ctx->eigen_device<Eigen::GpuDevice>().stream();
+        bool cube_mode = (p.boundaryMode == TEX_BOUNDARY_MODE_CUBE);
+
+        // Get input.
+        const Tensor& tex   = ctx->input(0);
+        const Tensor& uv    = ctx->input(1);
+        const Tensor& dy    = ctx->input(2);
+        const Tensor& uv_da = ctx->input(p.enableMip ? 3 : 2);
+        const Tensor& mip   = ctx->input(p.enableMip ? 4 : 2);
+
+        // Extract input dimensions.
+        p.n         = (uv.dims() > 0) ? uv.dim_size(0) : 0;
+        p.imgHeight = (uv.dims() > 1) ? uv.dim_size(1) : 0;
+        p.imgWidth  = (uv.dims() > 2) ? uv.dim_size(2) : 0;
+        p.texDepth  = (tex.dims() > 0) ? tex.dim_size(0) : 0;
+        if (!cube_mode)
+        {
+            p.texHeight = (tex.dims() > 1) ? tex.dim_size(1) : 0;
+            p.texWidth  = (tex.dims() > 2) ? tex.dim_size(2) : 0;
+            p.channels  = (tex.dims() > 3) ? tex.dim_size(3) : 0;
+        }
+        else
+        {
+            p.texHeight = (tex.dims() > 2) ? tex.dim_size(2) : 0;
+            p.texWidth  = (tex.dims() > 3) ? tex.dim_size(3) : 0;
+            p.channels  = (tex.dims() > 4) ? tex.dim_size(4) : 0;
+        }
+
+        // Sanity checks.
+        if (!cube_mode)
+        {
+            OP_REQUIRES(ctx, tex.dims() == 4 && tex.dim_size(0) > 0 && tex.dim_size(1) > 0 && tex.dim_size(2) > 0 && tex.dim_size(3) > 0, errors::InvalidArgument("tex must have shape[>0, >0, >0, >0]"));
+            OP_REQUIRES(ctx, uv.dims() == 4 && uv.dim_size(0) > 0 && uv.dim_size(1) > 0 && uv.dim_size(2) > 0 && uv.dim_size(3) == 2, errors::InvalidArgument("uv must have shape [>0, >0, >0, 2]"));
+        }
+        else
+        {
+            OP_REQUIRES(ctx, tex.dims() == 5 && tex.dim_size(0) > 0 && tex.dim_size(1) == 6 && tex.dim_size(2) > 0 && tex.dim_size(3) > 0 && tex.dim_size(4) > 0, errors::InvalidArgument("tex must have shape[>0, 6, >0, >0, >0] in cube map mode"));
+            OP_REQUIRES(ctx, uv.dims() == 4 && uv.dim_size(0) > 0 && uv.dim_size(1) > 0 && uv.dim_size(2) > 0 && uv.dim_size(3) == 3, errors::InvalidArgument("uv must have shape [>0, >0, >0, 3] in cube map mode"));
+            OP_REQUIRES(ctx, tex.dim_size(2) == tex.dim_size(3), errors::InvalidArgument("texture shape must be square in cube map mode"));
+        }
+        OP_REQUIRES(ctx, tex.dim_size(0) == 1 || tex.dim_size(0) == p.n, errors::InvalidArgument("minibatch size mismatch between inputs tex, uv"));
+        OP_REQUIRES(ctx, dy.dims() == 4 && dy.dim_size(0) == p.n && dy.dim_size(1) == p.imgHeight && dy.dim_size(2) == p.imgWidth && dy.dim_size(3) == p.channels, errors::InvalidArgument("dy must have shape [minibatch_size, height, width, channels]"));
+        if (p.enableMip)
+        {
+            if (!cube_mode)
+                OP_REQUIRES(ctx, uv_da.dims() == 4 && uv_da.dim_size(0) == p.n && uv_da.dim_size(1) == p.imgHeight && uv_da.dim_size(2) == p.imgWidth && uv_da.dim_size(3) == 4, errors::InvalidArgument("uv_da must have shape [minibatch_size, height, width, 4]"));
+            else
+                OP_REQUIRES(ctx, uv_da.dims() == 4 && uv_da.dim_size(0) == p.n && uv_da.dim_size(1) == p.imgHeight && uv_da.dim_size(2) == p.imgWidth && uv_da.dim_size(3) == 6, errors::InvalidArgument("uv_da must have shape [minibatch_size, height, width, 6] in cube map mode"));
+        }
+
+        // Get input pointers.
+        p.tex[0] = tex.flat<float>().data();
+        p.uv = uv.flat<float>().data();
+        p.dy = dy.flat<float>().data();
+        p.uvDA = p.enableMip ? uv_da.flat<float>().data() : 0;
+        float* pmip = p.enableMip ? (float*)mip.flat<float>().data() : 0;
+
+        // Allocate output tensor for tex gradient.
+        Tensor* grad_tex_tensor = NULL;
+        TensorShape grad_tex_shape;
+        grad_tex_shape.AddDim(p.texDepth);
+        if (cube_mode)
+            grad_tex_shape.AddDim(6);
+        grad_tex_shape.AddDim(p.texHeight);
+        grad_tex_shape.AddDim(p.texWidth);
+        grad_tex_shape.AddDim(p.channels);
+        OP_REQUIRES_OK(ctx, ctx->allocate_output(0, grad_tex_shape, &grad_tex_tensor));
+        p.gradTex[0] = grad_tex_tensor->flat<float>().data();
+
+        // Allocate output tensor for uv gradient.
+        if (p.filterMode != TEX_MODE_NEAREST)
+        {
+            TensorShape grad_uv_shape;
+            Tensor* grad_uv_tensor = NULL;
+            grad_uv_shape.AddDim(p.n);
+            grad_uv_shape.AddDim(p.imgHeight);
+            grad_uv_shape.AddDim(p.imgWidth);
+            grad_uv_shape.AddDim(uv.dim_size(3));
+            OP_REQUIRES_OK(ctx, ctx->allocate_output(1, grad_uv_shape, &grad_uv_tensor));
+            p.gradUV = grad_uv_tensor->flat<float>().data();
+
+            // Allocate output tensor for uv_da gradient.
+            if (p.filterMode == TEX_MODE_LINEAR_MIPMAP_LINEAR)
+            {
+                Tensor* grad_uv_da_tensor = NULL;
+                grad_uv_shape.set_dim(3, uv_da.dim_size(3));
+                OP_REQUIRES_OK(ctx, ctx->allocate_output(2, grad_uv_shape, &grad_uv_da_tensor));
+                p.gradUVDA = grad_uv_da_tensor->flat<float>().data();
+            }
+        }
+
+        // Choose kernel variants based on channel count.
+        int channel_div_idx = 0;
+        if (!(p.channels & 3))
+            channel_div_idx = 2;  // Channel count divisible by 4.
+        else if (!(p.channels & 1))
+            channel_div_idx = 1;  // Channel count divisible by 2.
+
+        // Mip-related setup.
+        Tensor grad_mip_tensor;
+        float* pgradMip = 0;
+        if (p.enableMip)
+        {
+            // Generate mip offsets.
+            int mipOffsets[TEX_MAX_MIP_LEVEL];
+            int mipTotal = calculateMipInfo(ctx, p, mipOffsets);
+
+            // Get space for temporary mip gradients.
+            TensorShape grad_mip_shape;
+            grad_mip_shape.AddDim(mipTotal);
+            ctx->allocate_temp(DT_FLOAT, grad_mip_shape, &grad_mip_tensor);
+            pgradMip = grad_mip_tensor.flat<float>().data();
+            for (int i=1; i <= p.mipLevelMax; i++)
+            {
+                p.tex[i] = pmip + mipOffsets[i]; // Pointers to mip levels.
+                p.gradTex[i] = pgradMip + mipOffsets[i]; // Pointers to mip gradients.
+            }
+
+            // Clear mip gradients.
+            OP_CHECK_CUDA_ERROR(ctx, cudaMemsetAsync(pgradMip, 0, mipTotal * sizeof(float), stream));
+        }
+
+        // Initialize texture gradients to zero.
+        int texBytes = p.texHeight * p.texWidth * p.texDepth * p.channels * sizeof(float);
+        if (cube_mode)
+            texBytes *= 6;
+        OP_CHECK_CUDA_ERROR(ctx, cudaMemsetAsync(p.gradTex[0], 0, texBytes, stream));
+
+        // Verify that buffers are aligned to allow float2/float4 operations. Unused pointers are zero so always aligned.
+        if (!cube_mode)
+        {
+            OP_REQUIRES(ctx, !((uintptr_t)p.uv       & 7), errors::Internal("uv input tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.gradUV   & 7), errors::Internal("grad_uv output tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.uvDA     & 15), errors::Internal("uv_da input tensor not aligned to float4"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.gradUVDA & 15), errors::Internal("grad_uv_da output tensor not aligned to float4"));
+        }
+        else
+        {
+            OP_REQUIRES(ctx, !((uintptr_t)p.uvDA     & 7), errors::Internal("uv_da input tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.gradUVDA & 7), errors::Internal("grad_uv_da output tensor not aligned to float2"));
+        }
+        if ((p.channels & 3) == 0)
+        {
+            OP_REQUIRES(ctx, !((uintptr_t)p.tex[0]     & 15), errors::Internal("tex input tensor not aligned to float4"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.gradTex[0] & 15), errors::Internal("grad_tex output tensor not aligned to float4"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.dy         & 15), errors::Internal("dy input tensor not aligned to float4"));
+            OP_REQUIRES(ctx, !((uintptr_t)pmip         & 15), errors::Internal("mip input tensor not aligned to float4"));
+            OP_REQUIRES(ctx, !((uintptr_t)pgradMip     & 15), errors::Internal("internal mip gradient tensor not aligned to float4"));
+        }
+        if ((p.channels & 1) == 0)
+        {
+            OP_REQUIRES(ctx, !((uintptr_t)p.tex[0]     & 7), errors::Internal("tex input tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.gradTex[0] & 7), errors::Internal("grad_tex output tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)p.dy         & 7), errors::Internal("dy output tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)pmip         & 7), errors::Internal("mip input tensor not aligned to float2"));
+            OP_REQUIRES(ctx, !((uintptr_t)pgradMip     & 7), errors::Internal("internal mip gradient tensor not aligned to float2"));
+        }
+
+        // Choose launch parameters for main gradient kernel.
+        void* args[] = {&p};
+        dim3 blockSize = getLaunchBlockSize(TEX_GRAD_MAX_KERNEL_BLOCK_WIDTH, TEX_GRAD_MAX_KERNEL_BLOCK_HEIGHT, p.imgWidth, p.imgHeight);
+        dim3 gridSize  = getLaunchGridSize(blockSize, p.imgWidth, p.imgHeight, p.n);
+
+        void* func_tbl[TEX_MODE_COUNT * 2] = {
+            (void*)TextureGradKernelNearest,
+            (void*)TextureGradKernelLinear,
+            (void*)TextureGradKernelLinearMipmapNearest,
+            (void*)TextureGradKernelLinearMipmapLinear,
+            (void*)TextureGradKernelCubeNearest,
+            (void*)TextureGradKernelCubeLinear,
+            (void*)TextureGradKernelCubeLinearMipmapNearest,
+            (void*)TextureGradKernelCubeLinearMipmapLinear,
+        };
+
+        // Function index.
+        int func_idx = p.filterMode;
+        if (cube_mode)
+            func_idx += TEX_MODE_COUNT;
+
+        // Launch main gradient kernel.
+        OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel(func_tbl[func_idx], gridSize, blockSize, args, 0, stream));
+
+        // Launch kernel to pull gradients from mip levels.
+        if (p.enableMip)
+        {
+            dim3 blockSize = getLaunchBlockSize(TEX_GRAD_MAX_MIP_KERNEL_BLOCK_WIDTH, TEX_GRAD_MAX_MIP_KERNEL_BLOCK_HEIGHT, p.texWidth, p.texHeight);
+            dim3 gridSize  = getLaunchGridSize(blockSize, p.texWidth, p.texHeight, p.texDepth * (cube_mode ? 6 : 1));
+            int sharedBytes = blockSize.x * blockSize.y * p.channels * sizeof(float);
+
+            void* mip_grad_func_tbl[3] = { (void*)MipGradKernel1, (void*)MipGradKernel2, (void*)MipGradKernel4 };
+            OP_CHECK_CUDA_ERROR(ctx, cudaLaunchKernel(mip_grad_func_tbl[channel_div_idx], gridSize, blockSize, args, sharedBytes, stream));
+        }
+    }
+};
+
+REGISTER_OP("TextureGradNearest")
+    .Input      ("tex: float")
+    .Input      ("uv: float")
+    .Input      ("dy: float")
+    .Output     ("grad_tex: float")
+    .Attr       ("filter_mode: int")
+    .Attr       ("boundary_mode: int");
+
+REGISTER_OP("TextureGradLinear")
+    .Input      ("tex: float")
+    .Input      ("uv: float")
+    .Input      ("dy: float")
+    .Output     ("grad_tex: float")
+    .Output     ("grad_uv: float")
+    .Attr       ("filter_mode: int")
+    .Attr       ("boundary_mode: int");
+
+REGISTER_OP("TextureGradLinearMipmapNearest")
+    .Input      ("tex: float")
+    .Input      ("uv: float")
+    .Input      ("dy: float")
+    .Input      ("uv_da: float")
+    .Input      ("mip: float")
+    .Output     ("grad_tex: float")
+    .Output     ("grad_uv: float")
+    .Attr       ("filter_mode: int")
+    .Attr       ("boundary_mode: int")
+    .Attr       ("max_mip_level: int");
+    
+REGISTER_OP("TextureGradLinearMipmapLinear")
+    .Input      ("tex: float")
+    .Input      ("uv: float")
+    .Input      ("dy: float")
+    .Input      ("uv_da: float")
+    .Input      ("mip: float")
+    .Output     ("grad_tex: float")
+    .Output     ("grad_uv: float")
+    .Output     ("grad_uv_da: float")
+    .Attr       ("filter_mode: int")
+    .Attr       ("boundary_mode: int")
+    .Attr       ("max_mip_level: int");
+    
+REGISTER_KERNEL_BUILDER(Name("TextureGradNearest")            .Device(DEVICE_GPU), TextureGradOp);
+REGISTER_KERNEL_BUILDER(Name("TextureGradLinear")             .Device(DEVICE_GPU), TextureGradOp);
+REGISTER_KERNEL_BUILDER(Name("TextureGradLinearMipmapNearest").Device(DEVICE_GPU), TextureGradOp);
+REGISTER_KERNEL_BUILDER(Name("TextureGradLinearMipmapLinear") .Device(DEVICE_GPU), TextureGradOp);
+        
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/__init__.py b/extensions/nvdiffrast/nvdiffrast/torch/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..d28f95e7a9e423b5efb322c39e343a069caf0fe8
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/__init__.py
@@ -0,0 +1,10 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+from .ops import RasterizeCudaContext, RasterizeGLContext, get_log_level, set_log_level, rasterize, DepthPeeler, interpolate, texture, texture_construct_mip, antialias, antialias_construct_topology_hash
+__all__ = ["RasterizeCudaContext", "RasterizeGLContext", "get_log_level", "set_log_level", "rasterize", "DepthPeeler", "interpolate", "texture", "texture_construct_mip", "antialias", "antialias_construct_topology_hash"]
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/ops.py b/extensions/nvdiffrast/nvdiffrast/torch/ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..edf8540fda5aed6736a72b44b993031157a9cf4b
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/ops.py
@@ -0,0 +1,734 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+import importlib
+import logging
+import numpy as np
+import os
+import torch
+import torch.utils.cpp_extension
+from . import _C
+
+#----------------------------------------------------------------------------
+# C++/Cuda plugin compiler/loader.
+
+_cached_plugin = {}
+def _get_plugin(gl=False):
+    assert isinstance(gl, bool)
+    
+    # Modified with precompiled torch CUDA extension
+    if not gl:
+        return _C
+
+    # Return cached plugin if already loaded.
+    if _cached_plugin.get(gl, None) is not None:
+        return _cached_plugin[gl]
+
+    # Make sure we can find the necessary compiler and libary binaries.
+    if os.name == 'nt':
+        lib_dir = os.path.dirname(__file__) + r"\..\lib"
+        def find_cl_path():
+            import glob
+            def get_sort_key(x):
+                # Primary criterion is VS version, secondary is edition, third is internal MSVC version.
+                x = x.split('\\')[3:]
+                x[1] = {'BuildTools': '~0', 'Community': '~1', 'Pro': '~2', 'Professional': '~3', 'Enterprise': '~4'}.get(x[1], x[1])
+                return x
+            vs_relative_path = r"\Microsoft Visual Studio\*\*\VC\Tools\MSVC\*\bin\Hostx64\x64"
+            paths = glob.glob(r"C:\Program Files" + vs_relative_path)
+            paths += glob.glob(r"C:\Program Files (x86)" + vs_relative_path)
+            if paths:
+                return sorted(paths, key=get_sort_key)[-1]
+
+        # If cl.exe is not on path, try to find it.
+        if os.system("where cl.exe >nul 2>nul") != 0:
+            cl_path = find_cl_path()
+            if cl_path is None:
+                raise RuntimeError("Could not locate a supported Microsoft Visual C++ installation")
+            os.environ['PATH'] += ';' + cl_path
+
+    # Compiler options.
+    common_opts = ['-DNVDR_TORCH']
+    cc_opts = []
+    if os.name == 'nt':
+        cc_opts += ['/wd4067', '/wd4624'] # Disable warnings in torch headers.
+
+    # Linker options for the GL-interfacing plugin.
+    ldflags = []
+    if gl:
+        if os.name == 'posix':
+            ldflags = ['-lGL', '-lEGL']
+        elif os.name == 'nt':
+            libs = ['gdi32', 'opengl32', 'user32', 'setgpu']
+            ldflags = ['/LIBPATH:' + lib_dir] + ['/DEFAULTLIB:' + x for x in libs]
+
+    # List of source files.
+    if gl:
+        source_files = [
+            '../common/common.cpp',
+            '../common/glutil.cpp',
+            '../common/rasterize_gl.cpp',
+            'torch_bindings_gl.cpp',
+            'torch_rasterize_gl.cpp',
+        ]
+    else:
+        source_files = [
+            '../common/cudaraster/impl/Buffer.cpp',
+            '../common/cudaraster/impl/CudaRaster.cpp',
+            '../common/cudaraster/impl/RasterImpl.cu',
+            '../common/cudaraster/impl/RasterImpl.cpp',
+            '../common/common.cpp',
+            '../common/rasterize.cu',
+            '../common/interpolate.cu',
+            '../common/texture.cu',
+            '../common/texture.cpp',
+            '../common/antialias.cu',
+            'torch_bindings.cpp',
+            'torch_rasterize.cpp',
+            'torch_interpolate.cpp',
+            'torch_texture.cpp',
+            'torch_antialias.cpp',
+        ]
+
+    # Some containers set this to contain old architectures that won't compile. We only need the one installed in the machine.
+    os.environ['TORCH_CUDA_ARCH_LIST'] = ''
+
+    # On Linux, show a warning if GLEW is being forcibly loaded when compiling the GL plugin.
+    if gl and (os.name == 'posix') and ('libGLEW' in os.environ.get('LD_PRELOAD', '')):
+        logging.getLogger('nvdiffrast').warning("Warning: libGLEW is being loaded via LD_PRELOAD, and will probably conflict with the OpenGL plugin")
+
+    # Try to detect if a stray lock file is left in cache directory and show a warning. This sometimes happens on Windows if the build is interrupted at just the right moment.
+    plugin_name = 'nvdiffrast_plugin' + ('_gl' if gl else '')
+    try:
+        lock_fn = os.path.join(torch.utils.cpp_extension._get_build_directory(plugin_name, False), 'lock')
+        if os.path.exists(lock_fn):
+            logging.getLogger('nvdiffrast').warning("Lock file exists in build directory: '%s'" % lock_fn)
+    except:
+        pass
+
+    # Speed up compilation on Windows.
+    if os.name == 'nt':
+        # Skip telemetry sending step in vcvarsall.bat
+        os.environ['VSCMD_SKIP_SENDTELEMETRY'] = '1'
+
+        # Opportunistically patch distutils to cache MSVC environments.
+        try:
+            import distutils._msvccompiler
+            import functools
+            if not hasattr(distutils._msvccompiler._get_vc_env, '__wrapped__'):
+                distutils._msvccompiler._get_vc_env = functools.lru_cache()(distutils._msvccompiler._get_vc_env)
+        except:
+            pass
+
+    # Compile and load.
+    source_paths = [os.path.join(os.path.dirname(__file__), fn) for fn in source_files]
+    torch.utils.cpp_extension.load(name=plugin_name, sources=source_paths, extra_cflags=common_opts+cc_opts, extra_cuda_cflags=common_opts+['-lineinfo'], extra_ldflags=ldflags, with_cuda=True, verbose=False)
+
+    # Import, cache, and return the compiled module.
+    _cached_plugin[gl] = importlib.import_module(plugin_name)
+    return _cached_plugin[gl]
+
+#----------------------------------------------------------------------------
+# Log level.
+#----------------------------------------------------------------------------
+
+def get_log_level():
+    '''Get current log level.
+
+    Returns:
+      Current log level in nvdiffrast. See `set_log_level()` for possible values.
+    '''
+    return _get_plugin().get_log_level()
+
+def set_log_level(level):
+    '''Set log level.
+
+    Log levels follow the convention on the C++ side of Torch:
+      0 = Info,
+      1 = Warning,
+      2 = Error,
+      3 = Fatal.
+    The default log level is 1.
+
+    Args:
+      level: New log level as integer. Internal nvdiffrast messages of this 
+             severity or higher will be printed, while messages of lower
+             severity will be silent.
+    '''
+    _get_plugin().set_log_level(level)
+
+#----------------------------------------------------------------------------
+# CudaRaster state wrapper.
+#----------------------------------------------------------------------------
+
+class RasterizeCudaContext:
+    def __init__(self, device=None):
+        '''Create a new Cuda rasterizer context.
+
+        The context is deleted and internal storage is released when the object is
+        destroyed.
+
+        Args:
+          device (Optional): Cuda device on which the context is created. Type can be
+                             `torch.device`, string (e.g., `'cuda:1'`), or int. If not
+                             specified, context will be created on currently active Cuda
+                             device.
+        Returns:
+          The newly created Cuda rasterizer context.
+        '''
+        if device is None:
+            cuda_device_idx = torch.cuda.current_device()
+        else:
+            with torch.cuda.device(device):
+                cuda_device_idx = torch.cuda.current_device()
+        self.cpp_wrapper = _get_plugin().RasterizeCRStateWrapper(cuda_device_idx)
+        self.output_db = True
+        self.active_depth_peeler = None
+
+#----------------------------------------------------------------------------
+# GL state wrapper.
+#----------------------------------------------------------------------------
+
+class RasterizeGLContext:
+    def __init__(self, output_db=True, mode='automatic', device=None):
+        '''Create a new OpenGL rasterizer context.
+
+        Creating an OpenGL context is a slow operation so you should usually reuse the same
+        context in all calls to `rasterize()` on the same CPU thread. The OpenGL context
+        is deleted when the object is destroyed.
+
+        Side note: When using the OpenGL context in a rasterization operation, the
+        context's internal framebuffer object is automatically enlarged to accommodate the
+        rasterization operation's output shape, but it is never shrunk in size until the
+        context is destroyed. Thus, if you need to rasterize, say, deep low-resolution
+        tensors and also shallow high-resolution tensors, you can conserve GPU memory by
+        creating two separate OpenGL contexts for these tasks. In this scenario, using the
+        same OpenGL context for both tasks would end up reserving GPU memory for a deep,
+        high-resolution output tensor.
+
+        Args:
+          output_db (bool): Compute and output image-space derivates of barycentrics.
+          mode: OpenGL context handling mode. Valid values are 'manual' and 'automatic'.
+          device (Optional): Cuda device on which the context is created. Type can be
+                             `torch.device`, string (e.g., `'cuda:1'`), or int. If not
+                             specified, context will be created on currently active Cuda
+                             device.
+        Returns:
+          The newly created OpenGL rasterizer context.
+        '''
+        assert output_db is True or output_db is False
+        assert mode in ['automatic', 'manual']
+        self.output_db = output_db
+        self.mode = mode
+        if device is None:
+            cuda_device_idx = torch.cuda.current_device()
+        else:
+            with torch.cuda.device(device):
+                cuda_device_idx = torch.cuda.current_device()
+        self.cpp_wrapper = _get_plugin(gl=True).RasterizeGLStateWrapper(output_db, mode == 'automatic', cuda_device_idx)
+        self.active_depth_peeler = None # For error checking only.
+
+    def set_context(self):
+        '''Set (activate) OpenGL context in the current CPU thread.
+           Only available if context was created in manual mode.
+        '''
+        assert self.mode == 'manual'
+        self.cpp_wrapper.set_context()
+
+    def release_context(self):
+        '''Release (deactivate) currently active OpenGL context.
+           Only available if context was created in manual mode.
+        '''
+        assert self.mode == 'manual'
+        self.cpp_wrapper.release_context()
+
+#----------------------------------------------------------------------------
+# Rasterize.
+#----------------------------------------------------------------------------
+
+class _rasterize_func(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, raster_ctx, pos, tri, resolution, ranges, grad_db, peeling_idx):
+        if isinstance(raster_ctx, RasterizeGLContext):
+            out, out_db = _get_plugin(gl=True).rasterize_fwd_gl(raster_ctx.cpp_wrapper, pos, tri, resolution, ranges, peeling_idx)
+        else:
+            out, out_db = _get_plugin().rasterize_fwd_cuda(raster_ctx.cpp_wrapper, pos, tri, resolution, ranges, peeling_idx)
+        ctx.save_for_backward(pos, tri, out)
+        ctx.saved_grad_db = grad_db
+        return out, out_db
+
+    @staticmethod
+    def backward(ctx, dy, ddb):
+        pos, tri, out = ctx.saved_tensors
+        if ctx.saved_grad_db:
+            g_pos = _get_plugin().rasterize_grad_db(pos, tri, out, dy, ddb)
+        else:
+            g_pos = _get_plugin().rasterize_grad(pos, tri, out, dy)
+        return None, g_pos, None, None, None, None, None
+
+# Op wrapper.
+def rasterize(glctx, pos, tri, resolution, ranges=None, grad_db=True):
+    '''Rasterize triangles.
+
+    All input tensors must be contiguous and reside in GPU memory except for
+    the `ranges` tensor that, if specified, has to reside in CPU memory. The
+    output tensors will be contiguous and reside in GPU memory.
+
+    Args:
+        glctx: Rasterizer context of type `RasterizeGLContext` or `RasterizeCudaContext`.
+        pos: Vertex position tensor with dtype `torch.float32`. To enable range
+             mode, this tensor should have a 2D shape [num_vertices, 4]. To enable
+             instanced mode, use a 3D shape [minibatch_size, num_vertices, 4].
+        tri: Triangle tensor with shape [num_triangles, 3] and dtype `torch.int32`.
+        resolution: Output resolution as integer tuple (height, width).
+        ranges: In range mode, tensor with shape [minibatch_size, 2] and dtype
+                `torch.int32`, specifying start indices and counts into `tri`.
+                Ignored in instanced mode.
+        grad_db: Propagate gradients of image-space derivatives of barycentrics
+                 into `pos` in backward pass. Ignored if using an OpenGL context that
+                 was not configured to output image-space derivatives.
+
+    Returns:
+        A tuple of two tensors. The first output tensor has shape [minibatch_size,
+        height, width, 4] and contains the main rasterizer output in order (u, v, z/w,
+        triangle_id). If the OpenGL context was configured to output image-space
+        derivatives of barycentrics, the second output tensor will also have shape
+        [minibatch_size, height, width, 4] and contain said derivatives in order
+        (du/dX, du/dY, dv/dX, dv/dY). Otherwise it will be an empty tensor with shape
+        [minibatch_size, height, width, 0].
+    '''
+    assert isinstance(glctx, (RasterizeGLContext, RasterizeCudaContext))
+    assert grad_db is True or grad_db is False
+    grad_db = grad_db and glctx.output_db
+
+    # Sanitize inputs.
+    assert isinstance(pos, torch.Tensor) and isinstance(tri, torch.Tensor)
+    resolution = tuple(resolution)
+    if ranges is None:
+        ranges = torch.empty(size=(0, 2), dtype=torch.int32, device='cpu')
+    else:
+        assert isinstance(ranges, torch.Tensor)
+
+    # Check that context is not currently reserved for depth peeling.
+    if glctx.active_depth_peeler is not None:
+        return RuntimeError("Cannot call rasterize() during depth peeling operation, use rasterize_next_layer() instead")
+
+    # Instantiate the function.
+    return _rasterize_func.apply(glctx, pos, tri, resolution, ranges, grad_db, -1)
+
+#----------------------------------------------------------------------------
+# Depth peeler context manager for rasterizing multiple depth layers.
+#----------------------------------------------------------------------------
+
+class DepthPeeler:
+    def __init__(self, glctx, pos, tri, resolution, ranges=None, grad_db=True):
+        '''Create a depth peeler object for rasterizing multiple depth layers.
+
+        Arguments are the same as in `rasterize()`.
+
+        Returns:
+          The newly created depth peeler.
+        '''
+        assert isinstance(glctx, (RasterizeGLContext, RasterizeCudaContext))
+        assert grad_db is True or grad_db is False
+        grad_db = grad_db and glctx.output_db
+
+        # Sanitize inputs as usual.
+        assert isinstance(pos, torch.Tensor) and isinstance(tri, torch.Tensor)
+        resolution = tuple(resolution)
+        if ranges is None:
+            ranges = torch.empty(size=(0, 2), dtype=torch.int32, device='cpu')
+        else:
+            assert isinstance(ranges, torch.Tensor)
+
+        # Store all the parameters.
+        self.raster_ctx = glctx
+        self.pos = pos
+        self.tri = tri
+        self.resolution = resolution
+        self.ranges = ranges
+        self.grad_db = grad_db
+        self.peeling_idx = None
+
+    def __enter__(self):
+        if self.raster_ctx is None:
+            raise RuntimeError("Cannot re-enter a terminated depth peeling operation")
+        if self.raster_ctx.active_depth_peeler is not None:
+            raise RuntimeError("Cannot have multiple depth peelers active simultaneously in a rasterization context")
+        self.raster_ctx.active_depth_peeler = self
+        self.peeling_idx = 0
+        return self
+
+    def __exit__(self, *args):
+        assert self.raster_ctx.active_depth_peeler is self
+        self.raster_ctx.active_depth_peeler = None
+        self.raster_ctx = None # Remove all references to input tensor so they're not left dangling.
+        self.pos = None
+        self.tri = None
+        self.resolution = None
+        self.ranges = None
+        self.grad_db = None
+        self.peeling_idx = None
+        return None
+
+    def rasterize_next_layer(self):
+        '''Rasterize next depth layer.
+
+        Operation is equivalent to `rasterize()` except that previously reported
+        surface points are culled away.
+
+        Returns:
+          A tuple of two tensors as in `rasterize()`.
+        '''
+        assert self.raster_ctx.active_depth_peeler is self
+        assert self.peeling_idx >= 0
+        result = _rasterize_func.apply(self.raster_ctx, self.pos, self.tri, self.resolution, self.ranges, self.grad_db, self.peeling_idx)
+        self.peeling_idx += 1
+        return result
+
+#----------------------------------------------------------------------------
+# Interpolate.
+#----------------------------------------------------------------------------
+
+# Output pixel differentials for at least some attributes.
+class _interpolate_func_da(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, attr, rast, tri, rast_db, diff_attrs_all, diff_attrs_list):
+        out, out_da = _get_plugin().interpolate_fwd_da(attr, rast, tri, rast_db, diff_attrs_all, diff_attrs_list)
+        ctx.save_for_backward(attr, rast, tri, rast_db)
+        ctx.saved_misc = diff_attrs_all, diff_attrs_list
+        return out, out_da
+
+    @staticmethod
+    def backward(ctx, dy, dda):
+        attr, rast, tri, rast_db = ctx.saved_tensors
+        diff_attrs_all, diff_attrs_list = ctx.saved_misc
+        g_attr, g_rast, g_rast_db = _get_plugin().interpolate_grad_da(attr, rast, tri, dy, rast_db, dda, diff_attrs_all, diff_attrs_list)
+        return g_attr, g_rast, None, g_rast_db, None, None
+
+# No pixel differential for any attribute.
+class _interpolate_func(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, attr, rast, tri):
+        out, out_da = _get_plugin().interpolate_fwd(attr, rast, tri)
+        ctx.save_for_backward(attr, rast, tri)
+        return out, out_da
+
+    @staticmethod
+    def backward(ctx, dy, _):
+        attr, rast, tri = ctx.saved_tensors
+        g_attr, g_rast = _get_plugin().interpolate_grad(attr, rast, tri, dy)
+        return g_attr, g_rast, None
+
+# Op wrapper.
+def interpolate(attr, rast, tri, rast_db=None, diff_attrs=None):
+    """Interpolate vertex attributes.
+
+    All input tensors must be contiguous and reside in GPU memory. The output tensors
+    will be contiguous and reside in GPU memory.
+
+    Args:
+        attr: Attribute tensor with dtype `torch.float32`. 
+              Shape is [num_vertices, num_attributes] in range mode, or 
+              [minibatch_size, num_vertices, num_attributes] in instanced mode.
+              Broadcasting is supported along the minibatch axis.
+        rast: Main output tensor from `rasterize()`.
+        tri: Triangle tensor with shape [num_triangles, 3] and dtype `torch.int32`.
+        rast_db: (Optional) Tensor containing image-space derivatives of barycentrics, 
+                 i.e., the second output tensor from `rasterize()`. Enables computing
+                 image-space derivatives of attributes.
+        diff_attrs: (Optional) List of attribute indices for which image-space
+                    derivatives are to be computed. Special value 'all' is equivalent
+                    to list [0, 1, ..., num_attributes - 1].
+
+    Returns:
+        A tuple of two tensors. The first output tensor contains interpolated
+        attributes and has shape [minibatch_size, height, width, num_attributes].
+        If `rast_db` and `diff_attrs` were specified, the second output tensor contains
+        the image-space derivatives of the selected attributes and has shape
+        [minibatch_size, height, width, 2 * len(diff_attrs)]. The derivatives of the
+        first selected attribute A will be on channels 0 and 1 as (dA/dX, dA/dY), etc.
+        Otherwise, the second output tensor will be an empty tensor with shape
+        [minibatch_size, height, width, 0].
+    """
+    # Sanitize the list of pixel differential attributes.
+    if diff_attrs is None:
+        diff_attrs = []
+    elif diff_attrs != 'all':
+        diff_attrs = np.asarray(diff_attrs, np.int32)
+        assert len(diff_attrs.shape) == 1
+        diff_attrs = diff_attrs.tolist()
+
+    diff_attrs_all = int(diff_attrs == 'all')
+    diff_attrs_list = [] if diff_attrs_all else diff_attrs
+
+    # Check inputs.
+    assert all(isinstance(x, torch.Tensor) for x in (attr, rast, tri))
+    if diff_attrs:
+        assert isinstance(rast_db, torch.Tensor)
+
+    # Choose stub.
+    if diff_attrs:
+        return _interpolate_func_da.apply(attr, rast, tri, rast_db, diff_attrs_all, diff_attrs_list)
+    else:
+        return _interpolate_func.apply(attr, rast, tri)
+
+#----------------------------------------------------------------------------
+# Texture
+#----------------------------------------------------------------------------
+
+# Linear-mipmap-linear and linear-mipmap-nearest: Mipmaps enabled.
+class _texture_func_mip(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, filter_mode, tex, uv, uv_da, mip_level_bias, mip_wrapper, filter_mode_enum, boundary_mode_enum, *mip_stack):
+        empty = torch.tensor([])
+        if uv_da is None:
+            uv_da = empty
+        if mip_level_bias is None:
+            mip_level_bias = empty
+        if mip_wrapper is None:
+            mip_wrapper = _get_plugin().TextureMipWrapper()
+        out = _get_plugin().texture_fwd_mip(tex, uv, uv_da, mip_level_bias, mip_wrapper, mip_stack, filter_mode_enum, boundary_mode_enum)
+        ctx.save_for_backward(tex, uv, uv_da, mip_level_bias, *mip_stack)
+        ctx.saved_misc = filter_mode, mip_wrapper, filter_mode_enum, boundary_mode_enum
+        return out
+
+    @staticmethod
+    def backward(ctx, dy):
+        tex, uv, uv_da, mip_level_bias, *mip_stack = ctx.saved_tensors
+        filter_mode, mip_wrapper, filter_mode_enum, boundary_mode_enum = ctx.saved_misc
+        if filter_mode == 'linear-mipmap-linear':
+            g_tex, g_uv, g_uv_da, g_mip_level_bias, g_mip_stack = _get_plugin().texture_grad_linear_mipmap_linear(tex, uv, dy, uv_da, mip_level_bias, mip_wrapper, mip_stack, filter_mode_enum, boundary_mode_enum)
+            return (None, g_tex, g_uv, g_uv_da, g_mip_level_bias, None, None, None) + tuple(g_mip_stack)
+        else: # linear-mipmap-nearest
+            g_tex, g_uv, g_mip_stack = _get_plugin().texture_grad_linear_mipmap_nearest(tex, uv, dy, uv_da, mip_level_bias, mip_wrapper, mip_stack, filter_mode_enum, boundary_mode_enum)
+            return (None, g_tex, g_uv, None, None, None, None, None) + tuple(g_mip_stack)
+
+# Linear and nearest: Mipmaps disabled.
+class _texture_func(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, filter_mode, tex, uv, filter_mode_enum, boundary_mode_enum):
+        out = _get_plugin().texture_fwd(tex, uv, filter_mode_enum, boundary_mode_enum)
+        ctx.save_for_backward(tex, uv)
+        ctx.saved_misc = filter_mode, filter_mode_enum, boundary_mode_enum
+        return out
+
+    @staticmethod
+    def backward(ctx, dy):
+        tex, uv = ctx.saved_tensors
+        filter_mode, filter_mode_enum, boundary_mode_enum = ctx.saved_misc
+        if filter_mode == 'linear':
+            g_tex, g_uv = _get_plugin().texture_grad_linear(tex, uv, dy, filter_mode_enum, boundary_mode_enum)
+            return None, g_tex, g_uv, None, None
+        else: # nearest
+            g_tex = _get_plugin().texture_grad_nearest(tex, uv, dy, filter_mode_enum, boundary_mode_enum)
+            return None, g_tex, None, None, None
+
+# Op wrapper.
+def texture(tex, uv, uv_da=None, mip_level_bias=None, mip=None, filter_mode='auto', boundary_mode='wrap', max_mip_level=None):
+    """Perform texture sampling.
+
+    All input tensors must be contiguous and reside in GPU memory. The output tensor
+    will be contiguous and reside in GPU memory.
+
+    Args:
+        tex: Texture tensor with dtype `torch.float32`. For 2D textures, must have shape
+             [minibatch_size, tex_height, tex_width, tex_channels]. For cube map textures,
+             must have shape [minibatch_size, 6, tex_height, tex_width, tex_channels] where
+             tex_width and tex_height are equal. Note that `boundary_mode` must also be set
+             to 'cube' to enable cube map mode. Broadcasting is supported along the minibatch axis.
+        uv: Tensor containing per-pixel texture coordinates. When sampling a 2D texture,
+            must have shape [minibatch_size, height, width, 2]. When sampling a cube map
+            texture, must have shape [minibatch_size, height, width, 3].
+        uv_da: (Optional) Tensor containing image-space derivatives of texture coordinates.
+               Must have same shape as `uv` except for the last dimension that is to be twice
+               as long.
+        mip_level_bias: (Optional) Per-pixel bias for mip level selection. If `uv_da` is omitted,
+                        determines mip level directly. Must have shape [minibatch_size, height, width].
+        mip: (Optional) Preconstructed mipmap stack from a `texture_construct_mip()` call, or a list
+                        of tensors specifying a custom mipmap stack. When specifying a custom mipmap stack,
+                        the tensors in the list must follow the same format as `tex` except for width and
+                        height that must follow the usual rules for mipmap sizes. The base level texture
+                        is still supplied in `tex` and must not be included in the list. Gradients of a
+                        custom mipmap stack are not automatically propagated to base texture but the mipmap
+                        tensors will receive gradients of their own. If a mipmap stack is not specified
+                        but the chosen filter mode requires it, the mipmap stack is constructed internally
+                        and discarded afterwards.
+        filter_mode: Texture filtering mode to be used. Valid values are 'auto', 'nearest',
+                     'linear', 'linear-mipmap-nearest', and 'linear-mipmap-linear'. Mode 'auto'
+                     selects 'linear' if neither `uv_da` or `mip_level_bias` is specified, and
+                     'linear-mipmap-linear' when at least one of them is specified, these being
+                     the highest-quality modes possible depending on the availability of the
+                     image-space derivatives of the texture coordinates or direct mip level information.
+        boundary_mode: Valid values are 'wrap', 'clamp', 'zero', and 'cube'. If `tex` defines a
+                       cube map, this must be set to 'cube'. The default mode 'wrap' takes fractional
+                       part of texture coordinates. Mode 'clamp' clamps texture coordinates to the
+                       centers of the boundary texels. Mode 'zero' virtually extends the texture with
+                       all-zero values in all directions.
+        max_mip_level: If specified, limits the number of mipmaps constructed and used in mipmap-based
+                       filter modes.
+
+    Returns:
+        A tensor containing the results of the texture sampling with shape
+        [minibatch_size, height, width, tex_channels]. Cube map fetches with invalid uv coordinates
+        (e.g., zero vectors) output all zeros and do not propagate gradients.
+    """
+
+    # Default filter mode.
+    if filter_mode == 'auto':
+        filter_mode = 'linear-mipmap-linear' if (uv_da is not None or mip_level_bias is not None) else 'linear'
+
+    # Sanitize inputs.
+    if max_mip_level is None:
+        max_mip_level = -1
+    else:
+        max_mip_level = int(max_mip_level)
+        assert max_mip_level >= 0
+
+    # Check inputs.
+    assert isinstance(tex, torch.Tensor) and isinstance(uv, torch.Tensor)
+    if 'mipmap' in filter_mode:
+        assert isinstance(uv_da, torch.Tensor) or isinstance(mip_level_bias, torch.Tensor)
+
+    # If mipping disabled via max level=0, we may as well use simpler filtering internally.
+    if max_mip_level == 0 and filter_mode in ['linear-mipmap-nearest', 'linear-mipmap-linear']:
+        filter_mode = 'linear'
+
+    # Convert filter mode to internal enumeration.
+    filter_mode_dict = {'nearest': 0, 'linear': 1, 'linear-mipmap-nearest': 2, 'linear-mipmap-linear': 3}
+    filter_mode_enum = filter_mode_dict[filter_mode]
+
+    # Convert boundary mode to internal enumeration.
+    boundary_mode_dict = {'cube': 0, 'wrap': 1, 'clamp': 2, 'zero': 3}
+    boundary_mode_enum = boundary_mode_dict[boundary_mode]
+
+    # Construct a mipmap if necessary.
+    if 'mipmap' in filter_mode:
+        mip_wrapper, mip_stack = None, []
+        if mip is not None:
+            assert isinstance(mip, (_get_plugin().TextureMipWrapper, list))
+            if isinstance(mip, list):
+                assert all(isinstance(x, torch.Tensor) for x in mip)
+                mip_stack = mip
+            else:
+                mip_wrapper = mip
+        else:
+            mip_wrapper = _get_plugin().texture_construct_mip(tex, max_mip_level, boundary_mode == 'cube')
+
+    # Choose stub.
+    if filter_mode == 'linear-mipmap-linear' or filter_mode == 'linear-mipmap-nearest':
+        return _texture_func_mip.apply(filter_mode, tex, uv, uv_da, mip_level_bias, mip_wrapper, filter_mode_enum, boundary_mode_enum, *mip_stack)
+    else:
+        return _texture_func.apply(filter_mode, tex, uv, filter_mode_enum, boundary_mode_enum)
+
+# Mipmap precalculation for cases where the texture stays constant.
+def texture_construct_mip(tex, max_mip_level=None, cube_mode=False):
+    """Construct a mipmap stack for a texture.
+
+    This function can be used for constructing a mipmap stack for a texture that is known to remain
+    constant. This avoids reconstructing it every time `texture()` is called.
+
+    Args:
+        tex: Texture tensor with the same constraints as in `texture()`.
+        max_mip_level: If specified, limits the number of mipmaps constructed.
+        cube_mode: Must be set to True if `tex` specifies a cube map texture.
+
+    Returns:
+        An opaque object containing the mipmap stack. This can be supplied in a call to `texture()` 
+        in the `mip` argument.
+    """
+
+    assert isinstance(tex, torch.Tensor)
+    assert cube_mode is True or cube_mode is False
+    if max_mip_level is None:
+        max_mip_level = -1
+    else:
+        max_mip_level = int(max_mip_level)
+        assert max_mip_level >= 0
+    return _get_plugin().texture_construct_mip(tex, max_mip_level, cube_mode)
+
+#----------------------------------------------------------------------------
+# Antialias.
+#----------------------------------------------------------------------------
+
+class _antialias_func(torch.autograd.Function):
+    @staticmethod
+    def forward(ctx, color, rast, pos, tri, topology_hash, pos_gradient_boost):
+        out, work_buffer = _get_plugin().antialias_fwd(color, rast, pos, tri, topology_hash)
+        ctx.save_for_backward(color, rast, pos, tri)
+        ctx.saved_misc = pos_gradient_boost, work_buffer
+        return out
+
+    @staticmethod
+    def backward(ctx, dy):
+        color, rast, pos, tri = ctx.saved_tensors
+        pos_gradient_boost, work_buffer = ctx.saved_misc
+        g_color, g_pos = _get_plugin().antialias_grad(color, rast, pos, tri, dy, work_buffer)
+        if pos_gradient_boost != 1.0:
+            g_pos = g_pos * pos_gradient_boost
+        return g_color, None, g_pos, None, None, None
+
+# Op wrapper.
+def antialias(color, rast, pos, tri, topology_hash=None, pos_gradient_boost=1.0):
+    """Perform antialiasing.
+
+    All input tensors must be contiguous and reside in GPU memory. The output tensor
+    will be contiguous and reside in GPU memory.
+
+    Note that silhouette edge determination is based on vertex indices in the triangle
+    tensor. For it to work properly, a vertex belonging to multiple triangles must be
+    referred to using the same vertex index in each triangle. Otherwise, nvdiffrast will always
+    classify the adjacent edges as silhouette edges, which leads to bad performance and
+    potentially incorrect gradients. If you are unsure whether your data is good, check
+    which pixels are modified by the antialias operation and compare to the example in the
+    documentation.
+
+    Args:
+        color: Input image to antialias with shape [minibatch_size, height, width, num_channels].
+        rast: Main output tensor from `rasterize()`.
+        pos: Vertex position tensor used in the rasterization operation.
+        tri: Triangle tensor used in the rasterization operation.
+        topology_hash: (Optional) Preconstructed topology hash for the triangle tensor. If not
+                       specified, the topology hash is constructed internally and discarded afterwards.
+        pos_gradient_boost: (Optional) Multiplier for gradients propagated to `pos`.
+
+    Returns:
+        A tensor containing the antialiased image with the same shape as `color` input tensor.
+    """
+
+    # Check inputs.
+    assert all(isinstance(x, torch.Tensor) for x in (color, rast, pos, tri))
+
+    # Construct topology hash unless provided by user.
+    if topology_hash is not None:
+        assert isinstance(topology_hash, _get_plugin().TopologyHashWrapper)
+    else:
+        topology_hash = _get_plugin().antialias_construct_topology_hash(tri)
+
+    # Instantiate the function.
+    return _antialias_func.apply(color, rast, pos, tri, topology_hash, pos_gradient_boost)
+
+# Topology hash precalculation for cases where the triangle array stays constant.
+def antialias_construct_topology_hash(tri):
+    """Construct a topology hash for a triangle tensor.
+
+    This function can be used for constructing a topology hash for a triangle tensor that is 
+    known to remain constant. This avoids reconstructing it every time `antialias()` is called.
+
+    Args:
+        tri: Triangle tensor with shape [num_triangles, 3]. Must be contiguous and reside in
+             GPU memory.
+
+    Returns:
+        An opaque object containing the topology hash. This can be supplied in a call to 
+        `antialias()` in the `topology_hash` argument.
+    """
+    assert isinstance(tri, torch.Tensor)
+    return _get_plugin().antialias_construct_topology_hash(tri)
+
+#----------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_antialias.cpp b/extensions/nvdiffrast/nvdiffrast/torch/torch_antialias.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..730a200e4b8ab29ffe73c7cca493d4b2f0c80f92
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_antialias.cpp
@@ -0,0 +1,243 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+#include "torch_types.h"
+#include "../common/common.h"
+#include "../common/antialias.h"
+
+//------------------------------------------------------------------------
+// Kernel prototypes.
+
+void AntialiasFwdMeshKernel         (const AntialiasKernelParams p);
+void AntialiasFwdDiscontinuityKernel(const AntialiasKernelParams p);
+void AntialiasFwdAnalysisKernel     (const AntialiasKernelParams p);
+void AntialiasGradKernel            (const AntialiasKernelParams p);
+
+//------------------------------------------------------------------------
+// Topology hash construction.
+
+TopologyHashWrapper antialias_construct_topology_hash(torch::Tensor tri)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(tri));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    AntialiasKernelParams p = {}; // Initialize all fields to zero.
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(tri);
+    NVDR_CHECK_CONTIGUOUS(tri);
+    NVDR_CHECK_I32(tri);
+    NVDR_CHECK(tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+
+    // Fill in kernel parameters.
+    p.numTriangles = tri.size(0);
+    p.numVertices = 0x7fffffff; // Let's not require vertex positions just to enable an error check.
+    p.tri = tri.data_ptr<int>();
+
+    // Kernel parameters.
+    p.allocTriangles = 64;
+    while (p.allocTriangles < p.numTriangles)
+        p.allocTriangles <<= 1; // Must be power of two.
+
+    // Construct the hash tensor and get pointer.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kInt32).device(torch::kCUDA);
+    torch::Tensor ev_hash = torch::zeros({(uint64_t)p.allocTriangles * AA_HASH_ELEMENTS_PER_TRIANGLE(p.allocTriangles) * 4}, opts);
+    p.evHash = (uint4*)(ev_hash.data_ptr<int>());
+
+    // Check alignment.
+    NVDR_CHECK(!((uintptr_t)p.evHash & 15), "ev_hash internal tensor not aligned to int4");
+
+    // Populate the hash.
+    void* args[] = {&p};
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)AntialiasFwdMeshKernel, (p.numTriangles - 1) / AA_MESH_KERNEL_THREADS_PER_BLOCK + 1, AA_MESH_KERNEL_THREADS_PER_BLOCK, args, 0, stream));
+
+    // Return.
+    TopologyHashWrapper hash_wrap;
+    hash_wrap.ev_hash = ev_hash;
+    return hash_wrap;
+}
+
+//------------------------------------------------------------------------
+// Forward op.
+
+std::tuple<torch::Tensor, torch::Tensor> antialias_fwd(torch::Tensor color, torch::Tensor rast, torch::Tensor pos, torch::Tensor tri, TopologyHashWrapper topology_hash_wrap)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(color));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    AntialiasKernelParams p = {}; // Initialize all fields to zero.
+    p.instance_mode = (pos.sizes().size() > 2) ? 1 : 0;
+    torch::Tensor& topology_hash = topology_hash_wrap.ev_hash; // Unwrap.
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(color, rast, pos, tri, topology_hash);
+    NVDR_CHECK_CONTIGUOUS(color, rast, pos, tri, topology_hash);
+    NVDR_CHECK_F32(color, rast, pos);
+    NVDR_CHECK_I32(tri, topology_hash);
+
+    // Sanity checks.
+    NVDR_CHECK(color.sizes().size() == 4 && color.size(0) > 0 && color.size(1) > 0 && color.size(2) > 0 && color.size(3) > 0, "color must have shape[>0, >0, >0, >0]");
+    NVDR_CHECK(rast.sizes().size() == 4 && rast.size(0) > 0 && rast.size(1) > 0 && rast.size(2) > 0 && rast.size(3) == 4, "rast must have shape[>0, >0, >0, 4]");
+    NVDR_CHECK(tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+    NVDR_CHECK(color.size(1) == rast.size(1) && color.size(2) == rast.size(2), "color and rast inputs must have same spatial dimensions");
+    if (p.instance_mode)
+    {
+        NVDR_CHECK(pos.sizes().size() == 3 && pos.size(0) > 0 && pos.size(1) > 0 && pos.size(2) == 4, "pos must have shape [>0, >0, 4] or [>0, 4]");
+        NVDR_CHECK(rast.size(0) == color.size(0) && pos.size(0) == color.size(0), "minibatch size mismatch between inputs color, rast, pos");
+    }
+    else
+    {
+        NVDR_CHECK(pos.sizes().size() == 2 && pos.size(0) > 0 && pos.size(1) == 4, "pos must have shape [>0, >0, 4] or [>0, 4]");
+        NVDR_CHECK(rast.size(0) == color.size(0), "minibatch size mismatch between inputs color, rast");
+    }
+
+    // Extract input dimensions.
+    p.numVertices  = pos.size(p.instance_mode ? 1 : 0);
+    p.numTriangles = tri.size(0);
+    p.n            = color.size(0);
+    p.height       = color.size(1);
+    p.width        = color.size(2);
+    p.channels     = color.size(3);
+
+    // Get input pointers.
+    p.color = color.data_ptr<float>();
+    p.rasterOut = rast.data_ptr<float>();
+    p.tri = tri.data_ptr<int>();
+    p.pos = pos.data_ptr<float>();
+    p.evHash = (uint4*)(topology_hash.data_ptr<int>());
+
+    // Misc parameters.
+    p.xh = .5f * (float)p.width;
+    p.yh = .5f * (float)p.height;
+
+    // Determine hash allocation size.
+    p.allocTriangles = 64;
+    while (p.allocTriangles < p.numTriangles)
+        p.allocTriangles <<= 1; // Must be power of two.
+
+    // Allocate output tensors.
+    torch::Tensor out = color.detach().clone(); // Use color as base.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
+    torch::Tensor work_buffer = torch::empty({p.n * p.width * p.height * 8 + 4}, opts); // 8 int for a maximum of two work items per pixel.
+    p.output = out.data_ptr<float>();
+    p.workBuffer = (int4*)(work_buffer.data_ptr<float>());
+
+    // Clear the work counters.
+    NVDR_CHECK_CUDA_ERROR(cudaMemsetAsync(p.workBuffer, 0, sizeof(int4), stream));
+
+    // Verify that buffers are aligned to allow float2/float4 operations.
+    NVDR_CHECK(!((uintptr_t)p.pos        & 15), "pos input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.rasterOut  &  7), "raster_out input tensor not aligned to float2");
+    NVDR_CHECK(!((uintptr_t)p.workBuffer & 15), "work_buffer internal tensor not aligned to int4");
+    NVDR_CHECK(!((uintptr_t)p.evHash     & 15), "topology_hash internal tensor not aligned to int4");
+
+    // Choose launch parameters for the discontinuity finder kernel and launch.
+    void* args[] = {&p};
+    dim3 blockSize(AA_DISCONTINUITY_KERNEL_BLOCK_WIDTH, AA_DISCONTINUITY_KERNEL_BLOCK_HEIGHT, 1);
+    dim3 gridSize = getLaunchGridSize(blockSize, p.width, p.height, p.n);
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)AntialiasFwdDiscontinuityKernel, gridSize, blockSize, args, 0, stream));
+
+    // Determine optimum block size for the persistent analysis kernel and launch.
+    int device = 0;
+    int numCTA = 0;
+    int numSM  = 0;
+    NVDR_CHECK_CUDA_ERROR(cudaGetDevice(&device));
+    NVDR_CHECK_CUDA_ERROR(cudaOccupancyMaxActiveBlocksPerMultiprocessor(&numCTA, (void*)AntialiasFwdAnalysisKernel, AA_ANALYSIS_KERNEL_THREADS_PER_BLOCK, 0));
+    NVDR_CHECK_CUDA_ERROR(cudaDeviceGetAttribute(&numSM, cudaDevAttrMultiProcessorCount, device));
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)AntialiasFwdAnalysisKernel, numCTA * numSM, AA_ANALYSIS_KERNEL_THREADS_PER_BLOCK, args, 0, stream));
+
+    // Return results.
+    return std::tuple<torch::Tensor, torch::Tensor>(out, work_buffer);
+}
+
+//------------------------------------------------------------------------
+// Gradient op.
+
+std::tuple<torch::Tensor, torch::Tensor> antialias_grad(torch::Tensor color, torch::Tensor rast, torch::Tensor pos, torch::Tensor tri, torch::Tensor dy, torch::Tensor work_buffer)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(color));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    AntialiasKernelParams p = {}; // Initialize all fields to zero.
+    p.instance_mode = (pos.sizes().size() > 2) ? 1 : 0;
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(color, rast, pos, tri, dy, work_buffer);
+    NVDR_CHECK_CONTIGUOUS(color, rast, pos, tri, work_buffer);
+    NVDR_CHECK_F32(color, rast, pos, dy, work_buffer);
+    NVDR_CHECK_I32(tri);
+
+    // Sanity checks.
+    NVDR_CHECK(dy.sizes().size() == 4 && dy.size(0) > 0 && dy.size(1) > 0 && dy.size(2) > 0 && dy.size(3) > 0, "dy must have shape[>0, >0, >0, >0]");
+    NVDR_CHECK(color.sizes().size() == 4 && color.size(0) > 0 && color.size(1) > 0 && color.size(2) > 0 && color.size(3) > 0, "color must have shape[>0, >0, >0, >0]");
+    NVDR_CHECK(rast.sizes().size() == 4 && rast.size(0) > 0 && rast.size(1) > 0 && rast.size(2) > 0 && rast.size(3) == 4, "raster_out must have shape[>0, >0, >0, 4]");
+    NVDR_CHECK(tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+    NVDR_CHECK(color.size(1) == rast.size(1) && color.size(2) == rast.size(2), "color and raster_out inputs must have same spatial dimensions");
+    NVDR_CHECK(color.size(1) == dy.size(1) && color.size(2) == dy.size(2) && color.size(3) == dy.size(3), "color and dy inputs must have same dimensions");
+    if (p.instance_mode)
+    {
+        NVDR_CHECK(pos.sizes().size() == 3 && pos.size(0) > 0 && pos.size(1) > 0 && pos.size(2) == 4, "pos must have shape [>0, >0, 4] or [>0, 4]");
+        NVDR_CHECK(rast.size(0) == color.size(0) && pos.size(0) == color.size(0), "minibatch size mismatch between inputs color, raster_out, pos");
+        NVDR_CHECK(dy.size(0) == color.size(0) && rast.size(0) == color.size(0) && pos.size(0) ==color.size(0), "minibatch size mismatch between inputs dy, color, raster_out, pos");
+    }
+    else
+    {
+        NVDR_CHECK(pos.sizes().size() == 2 && pos.size(0) > 0 && pos.size(1) == 4, "pos must have shape [>0, >0, 4] or [>0, 4]");
+        NVDR_CHECK(rast.size(0) == color.size(0), "minibatch size mismatch between inputs color, raster_out");
+        NVDR_CHECK(dy.size(0) == color.size(0) && rast.size(0) == color.size(0), "minibatch size mismatch between inputs dy, color, raster_out");
+    }
+
+    // Extract input dimensions.
+    p.numVertices  = pos.size(p.instance_mode ? 1 : 0);
+    p.numTriangles = tri.size(0);
+    p.n            = color.size(0);
+    p.height       = color.size(1);
+    p.width        = color.size(2);
+    p.channels     = color.size(3);
+
+    // Ensure dy is contiguous.
+    torch::Tensor dy_ = dy.contiguous();
+
+    // Get input pointers.
+    p.color = color.data_ptr<float>();
+    p.rasterOut = rast.data_ptr<float>();
+    p.tri = tri.data_ptr<int>();
+    p.pos = pos.data_ptr<float>();
+    p.dy = dy_.data_ptr<float>();
+    p.workBuffer = (int4*)(work_buffer.data_ptr<float>());
+
+    // Misc parameters.
+    p.xh = .5f * (float)p.width;
+    p.yh = .5f * (float)p.height;
+
+    // Allocate output tensors.
+    torch::Tensor grad_color = dy_.detach().clone(); // Use dy as base.
+    torch::Tensor grad_pos = torch::zeros_like(pos);
+    p.gradColor = grad_color.data_ptr<float>();
+    p.gradPos = grad_pos.data_ptr<float>();
+
+    // Clear gradient kernel work counter.
+    NVDR_CHECK_CUDA_ERROR(cudaMemsetAsync(&p.workBuffer[0].y, 0, sizeof(int), stream));
+
+    // Verify that buffers are aligned to allow float2/float4 operations.
+    NVDR_CHECK(!((uintptr_t)p.pos        & 15), "pos input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.workBuffer & 15), "work_buffer internal tensor not aligned to int4");
+
+    // Determine optimum block size for the gradient kernel and launch.
+    void* args[] = {&p};
+    int device = 0;
+    int numCTA = 0;
+    int numSM  = 0;
+    NVDR_CHECK_CUDA_ERROR(cudaGetDevice(&device));
+    NVDR_CHECK_CUDA_ERROR(cudaOccupancyMaxActiveBlocksPerMultiprocessor(&numCTA, (void*)AntialiasGradKernel, AA_GRAD_KERNEL_THREADS_PER_BLOCK, 0));
+    NVDR_CHECK_CUDA_ERROR(cudaDeviceGetAttribute(&numSM, cudaDevAttrMultiProcessorCount, device));
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)AntialiasGradKernel, numCTA * numSM, AA_GRAD_KERNEL_THREADS_PER_BLOCK, args, 0, stream));
+
+    // Return results.
+    return std::tuple<torch::Tensor, torch::Tensor>(grad_color, grad_pos);
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_bindings.cpp b/extensions/nvdiffrast/nvdiffrast/torch/torch_bindings.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..898e17e37b5ac559362732b1eaa118a64240dadb
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_bindings.cpp
@@ -0,0 +1,73 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+#include "torch_types.h"
+#include <tuple>
+
+//------------------------------------------------------------------------
+// Op prototypes. Return type macros for readability.
+
+#define OP_RETURN_T     torch::Tensor
+#define OP_RETURN_TT    std::tuple<torch::Tensor, torch::Tensor>
+#define OP_RETURN_TTT   std::tuple<torch::Tensor, torch::Tensor, torch::Tensor>
+#define OP_RETURN_TTTT  std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor>
+#define OP_RETURN_TTV   std::tuple<torch::Tensor, torch::Tensor, std::vector<torch::Tensor> >
+#define OP_RETURN_TTTTV std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, std::vector<torch::Tensor> >
+
+OP_RETURN_TT        rasterize_fwd_cuda                  (RasterizeCRStateWrapper& stateWrapper, torch::Tensor pos, torch::Tensor tri, std::tuple<int, int> resolution, torch::Tensor ranges, int peeling_idx);
+OP_RETURN_T         rasterize_grad                      (torch::Tensor pos, torch::Tensor tri, torch::Tensor out, torch::Tensor dy);
+OP_RETURN_T         rasterize_grad_db                   (torch::Tensor pos, torch::Tensor tri, torch::Tensor out, torch::Tensor dy, torch::Tensor ddb);
+OP_RETURN_TT        interpolate_fwd                     (torch::Tensor attr, torch::Tensor rast, torch::Tensor tri);
+OP_RETURN_TT        interpolate_fwd_da                  (torch::Tensor attr, torch::Tensor rast, torch::Tensor tri, torch::Tensor rast_db, bool diff_attrs_all, std::vector<int>& diff_attrs_vec);
+OP_RETURN_TT        interpolate_grad                    (torch::Tensor attr, torch::Tensor rast, torch::Tensor tri, torch::Tensor dy);
+OP_RETURN_TTT       interpolate_grad_da                 (torch::Tensor attr, torch::Tensor rast, torch::Tensor tri, torch::Tensor dy, torch::Tensor rast_db, torch::Tensor dda, bool diff_attrs_all, std::vector<int>& diff_attrs_vec);
+TextureMipWrapper   texture_construct_mip               (torch::Tensor tex, int max_mip_level, bool cube_mode);
+OP_RETURN_T         texture_fwd                         (torch::Tensor tex, torch::Tensor uv, int filter_mode, int boundary_mode);
+OP_RETURN_T         texture_fwd_mip                     (torch::Tensor tex, torch::Tensor uv, torch::Tensor uv_da, torch::Tensor mip_level_bias, TextureMipWrapper mip_wrapper, std::vector<torch::Tensor> mip_stack, int filter_mode, int boundary_mode);
+OP_RETURN_T         texture_grad_nearest                (torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, int filter_mode, int boundary_mode);
+OP_RETURN_TT        texture_grad_linear                 (torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, int filter_mode, int boundary_mode);
+OP_RETURN_TTV       texture_grad_linear_mipmap_nearest  (torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, torch::Tensor uv_da, torch::Tensor mip_level_bias, TextureMipWrapper mip_wrapper, std::vector<torch::Tensor> mip_stack, int filter_mode, int boundary_mode);
+OP_RETURN_TTTTV     texture_grad_linear_mipmap_linear   (torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, torch::Tensor uv_da, torch::Tensor mip_level_bias, TextureMipWrapper mip_wrapper, std::vector<torch::Tensor> mip_stack, int filter_mode, int boundary_mode);
+TopologyHashWrapper antialias_construct_topology_hash   (torch::Tensor tri);
+OP_RETURN_TT        antialias_fwd                       (torch::Tensor color, torch::Tensor rast, torch::Tensor pos, torch::Tensor tri, TopologyHashWrapper topology_hash);
+OP_RETURN_TT        antialias_grad                      (torch::Tensor color, torch::Tensor rast, torch::Tensor pos, torch::Tensor tri, torch::Tensor dy, torch::Tensor work_buffer);
+
+//------------------------------------------------------------------------
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    // State classes.
+    pybind11::class_<RasterizeCRStateWrapper>(m, "RasterizeCRStateWrapper").def(pybind11::init<int>());
+    pybind11::class_<TextureMipWrapper>(m, "TextureMipWrapper").def(pybind11::init<>());
+    pybind11::class_<TopologyHashWrapper>(m, "TopologyHashWrapper");
+
+    // Plumbing to torch/c10 logging system.
+    m.def("get_log_level", [](void)     { return FLAGS_caffe2_log_level;  }, "get log level");
+    m.def("set_log_level", [](int level){ FLAGS_caffe2_log_level = level; }, "set log level");
+
+    // Ops.
+    m.def("rasterize_fwd_cuda",                 &rasterize_fwd_cuda,                    "rasterize forward op (cuda)");
+    m.def("rasterize_grad",                     &rasterize_grad,                        "rasterize gradient op ignoring db gradients");
+    m.def("rasterize_grad_db",                  &rasterize_grad_db,                     "rasterize gradient op with db gradients");
+    m.def("interpolate_fwd",                    &interpolate_fwd,                       "interpolate forward op with attribute derivatives");
+    m.def("interpolate_fwd_da",                 &interpolate_fwd_da,                    "interpolate forward op without attribute derivatives");
+    m.def("interpolate_grad",                   &interpolate_grad,                      "interpolate gradient op with attribute derivatives");
+    m.def("interpolate_grad_da",                &interpolate_grad_da,                   "interpolate gradient op without attribute derivatives");
+    m.def("texture_construct_mip",              &texture_construct_mip,                 "texture mipmap construction");
+    m.def("texture_fwd",                        &texture_fwd,                           "texture forward op without mipmapping");
+    m.def("texture_fwd_mip",                    &texture_fwd_mip,                       "texture forward op with mipmapping");
+    m.def("texture_grad_nearest",               &texture_grad_nearest,                  "texture gradient op in nearest mode");
+    m.def("texture_grad_linear",                &texture_grad_linear,                   "texture gradient op in linear mode");
+    m.def("texture_grad_linear_mipmap_nearest", &texture_grad_linear_mipmap_nearest,    "texture gradient op in linear-mipmap-nearest mode");
+    m.def("texture_grad_linear_mipmap_linear",  &texture_grad_linear_mipmap_linear,     "texture gradient op in linear-mipmap-linear mode");
+    m.def("antialias_construct_topology_hash",  &antialias_construct_topology_hash,     "antialias topology hash construction");
+    m.def("antialias_fwd",                      &antialias_fwd,                         "antialias forward op");
+    m.def("antialias_grad",                     &antialias_grad,                        "antialias gradient op");
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_bindings_gl.cpp b/extensions/nvdiffrast/nvdiffrast/torch/torch_bindings_gl.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..5363e80297b9f9d5d212c890c8a455e60122366f
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_bindings_gl.cpp
@@ -0,0 +1,30 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+#include "torch_types.h"
+#include <tuple>
+
+//------------------------------------------------------------------------
+// Op prototypes.
+
+std::tuple<torch::Tensor, torch::Tensor> rasterize_fwd_gl(RasterizeGLStateWrapper& stateWrapper, torch::Tensor pos, torch::Tensor tri, std::tuple<int, int> resolution, torch::Tensor ranges, int peeling_idx);
+
+//------------------------------------------------------------------------
+
+PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
+    // State classes.
+    pybind11::class_<RasterizeGLStateWrapper>(m, "RasterizeGLStateWrapper").def(pybind11::init<bool, bool, int>())
+        .def("set_context",     &RasterizeGLStateWrapper::setContext)
+        .def("release_context", &RasterizeGLStateWrapper::releaseContext);
+
+    // Ops.
+    m.def("rasterize_fwd_gl", &rasterize_fwd_gl, "rasterize forward op (opengl)");
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_common.inl b/extensions/nvdiffrast/nvdiffrast/torch/torch_common.inl
new file mode 100644
index 0000000000000000000000000000000000000000..74dea41528822294878d9ee5d36d1230d1df7ae6
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_common.inl
@@ -0,0 +1,29 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#pragma once
+#include "../common/framework.h"
+
+//------------------------------------------------------------------------
+// Input check helpers.
+//------------------------------------------------------------------------
+
+#ifdef _MSC_VER
+#define __func__ __FUNCTION__
+#endif
+
+#define NVDR_CHECK_DEVICE(...) do { TORCH_CHECK(at::cuda::check_device({__VA_ARGS__}), __func__, "(): Inputs " #__VA_ARGS__ " must reside on the same GPU device") } while(0)
+#define NVDR_CHECK_CPU(...) do { nvdr_check_cpu({__VA_ARGS__}, __func__, "(): Inputs " #__VA_ARGS__ " must reside on CPU"); } while(0)
+#define NVDR_CHECK_CONTIGUOUS(...) do { nvdr_check_contiguous({__VA_ARGS__}, __func__, "(): Inputs " #__VA_ARGS__ " must be contiguous tensors"); } while(0)
+#define NVDR_CHECK_F32(...) do { nvdr_check_f32({__VA_ARGS__}, __func__, "(): Inputs " #__VA_ARGS__ " must be float32 tensors"); } while(0)
+#define NVDR_CHECK_I32(...) do { nvdr_check_i32({__VA_ARGS__}, __func__, "(): Inputs " #__VA_ARGS__ " must be int32 tensors"); } while(0)
+inline void nvdr_check_cpu(at::ArrayRef<at::Tensor> ts,        const char* func, const char* err_msg) { for (const at::Tensor& t : ts) TORCH_CHECK(t.device().type() == c10::DeviceType::CPU, func, err_msg); }
+inline void nvdr_check_contiguous(at::ArrayRef<at::Tensor> ts, const char* func, const char* err_msg) { for (const at::Tensor& t : ts) TORCH_CHECK(t.is_contiguous(), func, err_msg); }
+inline void nvdr_check_f32(at::ArrayRef<at::Tensor> ts,        const char* func, const char* err_msg) { for (const at::Tensor& t : ts) TORCH_CHECK(t.dtype() == torch::kFloat32, func, err_msg); }
+inline void nvdr_check_i32(at::ArrayRef<at::Tensor> ts,        const char* func, const char* err_msg) { for (const at::Tensor& t : ts) TORCH_CHECK(t.dtype() == torch::kInt32, func, err_msg); }
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_interpolate.cpp b/extensions/nvdiffrast/nvdiffrast/torch/torch_interpolate.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..b2c99fccfe0b11b71018e2c0ddcf637a337522b8
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_interpolate.cpp
@@ -0,0 +1,250 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+#include "../common/common.h"
+#include "../common/interpolate.h"
+
+//------------------------------------------------------------------------
+// Kernel prototypes.
+
+void InterpolateFwdKernel   (const InterpolateKernelParams p);
+void InterpolateFwdKernelDa (const InterpolateKernelParams p);
+void InterpolateGradKernel  (const InterpolateKernelParams p);
+void InterpolateGradKernelDa(const InterpolateKernelParams p);
+
+//------------------------------------------------------------------------
+// Helper
+
+static void set_diff_attrs(InterpolateKernelParams& p, bool diff_attrs_all, std::vector<int>& diff_attrs_vec)
+{
+    if (diff_attrs_all)
+    {
+        p.numDiffAttr = p.numAttr;
+        p.diff_attrs_all = 1;
+    }
+    else
+    {
+        NVDR_CHECK(diff_attrs_vec.size() <= IP_MAX_DIFF_ATTRS, "too many entries in diff_attrs list (increase IP_MAX_DIFF_ATTRS)");
+        p.numDiffAttr = diff_attrs_vec.size();
+        memcpy(p.diffAttrs, &diff_attrs_vec[0], diff_attrs_vec.size()*sizeof(int));
+    }
+}
+
+//------------------------------------------------------------------------
+// Forward op.
+
+std::tuple<torch::Tensor, torch::Tensor> interpolate_fwd_da(torch::Tensor attr, torch::Tensor rast, torch::Tensor tri, torch::Tensor rast_db, bool diff_attrs_all, std::vector<int>& diff_attrs_vec)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(attr));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    InterpolateKernelParams p = {}; // Initialize all fields to zero.
+    bool enable_da = (rast_db.defined()) && (diff_attrs_all || !diff_attrs_vec.empty());
+    p.instance_mode = (attr.sizes().size() > 2) ? 1 : 0;
+
+    // Check inputs.
+    if (enable_da)
+    {
+        NVDR_CHECK_DEVICE(attr, rast, tri, rast_db);
+        NVDR_CHECK_CONTIGUOUS(attr, rast, tri, rast_db);
+        NVDR_CHECK_F32(attr, rast, rast_db);
+        NVDR_CHECK_I32(tri);
+    }
+    else
+    {
+        NVDR_CHECK_DEVICE(attr, rast, tri);
+        NVDR_CHECK_CONTIGUOUS(attr, rast, tri);
+        NVDR_CHECK_F32(attr, rast);
+        NVDR_CHECK_I32(tri);
+    }
+
+    // Sanity checks.
+    NVDR_CHECK(rast.sizes().size() == 4 && rast.size(0) > 0 && rast.size(1) > 0 && rast.size(2) > 0 && rast.size(3) == 4, "rast must have shape[>0, >0, >0, 4]");
+    NVDR_CHECK( tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+    NVDR_CHECK((attr.sizes().size() == 2 || attr.sizes().size() == 3) && attr.size(0) > 0 && attr.size(1) > 0 && (attr.sizes().size() == 2 || attr.size(2) > 0), "attr must have shape [>0, >0, >0] or [>0, >0]");
+    if (p.instance_mode)
+        NVDR_CHECK(attr.size(0) == rast.size(0) || attr.size(0) == 1, "minibatch size mismatch between inputs rast, attr");
+    if (enable_da)
+    {
+        NVDR_CHECK(rast_db.sizes().size() == 4 && rast_db.size(0) > 0 && rast_db.size(1) > 0 && rast_db.size(2) > 0 && rast_db.size(3) == 4, "rast_db must have shape[>0, >0, >0, 4]");
+        NVDR_CHECK(rast_db.size(1) == rast.size(1) && rast_db.size(2) == rast.size(2), "spatial size mismatch between inputs rast and rast_db");
+        NVDR_CHECK(rast_db.size(0) == rast.size(0), "minibatch size mismatch between inputs rast, rast_db");
+    }
+
+    // Extract input dimensions.
+    p.numVertices  = attr.size(p.instance_mode ? 1 : 0);
+    p.numAttr      = attr.size(p.instance_mode ? 2 : 1);
+    p.numTriangles = tri.size(0);
+    p.height       = rast.size(1);
+    p.width        = rast.size(2);
+    p.depth        = rast.size(0);
+
+    // Set attribute pixel differential info if enabled, otherwise leave as zero.
+    if (enable_da)
+        set_diff_attrs(p, diff_attrs_all, diff_attrs_vec);
+    else
+        p.numDiffAttr = 0;
+
+    // Get input pointers.
+    p.attr = attr.data_ptr<float>();
+    p.rast = rast.data_ptr<float>();
+    p.tri = tri.data_ptr<int>();
+    p.rastDB = enable_da ? rast_db.data_ptr<float>() : NULL;
+    p.attrBC = (p.instance_mode && attr.size(0) == 1) ? 1 : 0;
+
+    // Allocate output tensors.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
+    torch::Tensor out = torch::empty({p.depth, p.height, p.width, p.numAttr}, opts);
+    torch::Tensor out_da = torch::empty({p.depth, p.height, p.width, p.numDiffAttr * 2}, opts);
+
+    p.out = out.data_ptr<float>();
+    p.outDA = enable_da ? out_da.data_ptr<float>() : NULL;
+
+    // Verify that buffers are aligned to allow float2/float4 operations.
+    NVDR_CHECK(!((uintptr_t)p.rast   & 15), "rast input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.rastDB & 15), "rast_db input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.outDA  &  7), "out_da output tensor not aligned to float2");
+
+    // Choose launch parameters.
+    dim3 blockSize = getLaunchBlockSize(IP_FWD_MAX_KERNEL_BLOCK_WIDTH, IP_FWD_MAX_KERNEL_BLOCK_HEIGHT, p.width, p.height);
+    dim3 gridSize  = getLaunchGridSize(blockSize, p.width, p.height, p.depth);
+
+    // Launch CUDA kernel.
+    void* args[] = {&p};
+    void* func = enable_da ? (void*)InterpolateFwdKernelDa : (void*)InterpolateFwdKernel;
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel(func, gridSize, blockSize, args, 0, stream));
+
+    // Return results.
+    return std::tuple<torch::Tensor, torch::Tensor>(out, out_da);
+}
+
+// Version without derivatives.
+std::tuple<torch::Tensor, torch::Tensor> interpolate_fwd(torch::Tensor attr, torch::Tensor rast, torch::Tensor tri)
+{
+    std::vector<int> empty_vec;
+    torch::Tensor empty_tensor;
+    return interpolate_fwd_da(attr, rast, tri, empty_tensor, false, empty_vec);
+}
+
+//------------------------------------------------------------------------
+// Gradient op.
+
+std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> interpolate_grad_da(torch::Tensor attr, torch::Tensor rast, torch::Tensor tri, torch::Tensor dy, torch::Tensor rast_db, torch::Tensor dda, bool diff_attrs_all, std::vector<int>& diff_attrs_vec)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(attr));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    InterpolateKernelParams p = {}; // Initialize all fields to zero.
+    bool enable_da = (rast_db.defined()) && (diff_attrs_all || !diff_attrs_vec.empty());
+    p.instance_mode = (attr.sizes().size() > 2) ? 1 : 0;
+
+    // Check inputs.
+    if (enable_da)
+    {
+        NVDR_CHECK_DEVICE(attr, rast, tri, dy, rast_db, dda);
+        NVDR_CHECK_CONTIGUOUS(attr, rast, tri, rast_db);
+        NVDR_CHECK_F32(attr, rast, dy, rast_db, dda);
+        NVDR_CHECK_I32(tri);
+    }
+    else
+    {
+        NVDR_CHECK_DEVICE(attr, rast, tri, dy);
+        NVDR_CHECK_CONTIGUOUS(attr, rast, tri);
+        NVDR_CHECK_F32(attr, rast, dy);
+        NVDR_CHECK_I32(tri);
+    }
+
+    // Depth of attributes.
+    int attr_depth = p.instance_mode ? (attr.sizes().size() > 1 ? attr.size(0) : 0) : 1;
+
+    // Sanity checks.
+    NVDR_CHECK(rast.sizes().size() == 4 && rast.size(0) > 0 && rast.size(1) > 0 && rast.size(2) > 0 && rast.size(3) == 4, "rast must have shape[>0, >0, >0, 4]");
+    NVDR_CHECK(tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+    NVDR_CHECK((attr.sizes().size() == 2 || attr.sizes().size() == 3) && attr.size(0) > 0 && attr.size(1) > 0 && (attr.sizes().size() == 2 || attr.size(2) > 0), "attr must have shape [>0, >0, >0] or [>0, >0]");
+    NVDR_CHECK(dy.sizes().size() == 4 && dy.size(0) > 0 && dy.size(1) == rast.size(1) && dy.size(2) == rast.size(2) && dy.size(3) > 0, "dy must have shape [>0, height, width, >0]");
+    NVDR_CHECK(dy.size(3) == attr.size(attr.sizes().size() - 1), "argument count mismatch between inputs dy, attr");
+    NVDR_CHECK((attr_depth == rast.size(0) || attr_depth == 1) && dy.size(0) == rast.size(0), "minibatch size mismatch between inputs rast, dy, attr");
+    if (enable_da)
+    {
+        NVDR_CHECK(dda.sizes().size() == 4 && dda.size(0) > 0 && dda.size(1) == rast.size(1) && dda.size(2) == rast.size(2), "dda must have shape [>0, height, width, ?]");
+        NVDR_CHECK(dda.size(0) == rast.size(0), "minibatch size mismatch between rast, dda");
+        NVDR_CHECK(rast_db.sizes().size() == 4 && rast_db.size(0) > 0 && rast_db.size(1) > 0 && rast_db.size(2) > 0 && rast_db.size(3) == 4, "rast_db must have shape[>0, >0, >0, 4]");
+        NVDR_CHECK(rast_db.size(1) == rast.size(1) && rast_db.size(2) == rast.size(2), "spatial size mismatch between inputs rast and rast_db");
+        NVDR_CHECK(rast_db.size(0) == rast.size(0), "minibatch size mismatch between inputs rast, rast_db");
+    }
+
+    // Extract input dimensions.
+    p.numVertices  = attr.size(p.instance_mode ? 1 : 0);
+    p.numAttr      = attr.size(p.instance_mode ? 2 : 1);
+    p.numTriangles = tri.size(0);
+    p.height       = rast.size(1);
+    p.width        = rast.size(2);
+    p.depth        = rast.size(0);
+
+    // Ensure gradients are contiguous.
+    torch::Tensor dy_ = dy.contiguous();
+    torch::Tensor dda_;
+    if (enable_da)
+        dda_ = dda.contiguous();
+
+    // Set attribute pixel differential info if enabled, otherwise leave as zero.
+    if (enable_da)
+        set_diff_attrs(p, diff_attrs_all, diff_attrs_vec);
+    else
+        p.numDiffAttr = 0;
+
+    // Get input pointers.
+    p.attr = attr.data_ptr<float>();
+    p.rast = rast.data_ptr<float>();
+    p.tri = tri.data_ptr<int>();
+    p.dy = dy_.data_ptr<float>();
+    p.rastDB = enable_da ? rast_db.data_ptr<float>() : NULL;
+    p.dda = enable_da ? dda_.data_ptr<float>() : NULL;
+    p.attrBC = (p.instance_mode && attr_depth < p.depth) ? 1 : 0;
+
+    // Allocate output tensors.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
+    torch::Tensor gradAttr = torch::zeros_like(attr);
+    torch::Tensor gradRaster = torch::empty_like(rast);
+    torch::Tensor gradRasterDB;
+    if (enable_da)
+        gradRasterDB = torch::empty_like(rast_db);
+
+    p.gradAttr = gradAttr.data_ptr<float>();
+    p.gradRaster = gradRaster.data_ptr<float>();
+    p.gradRasterDB = enable_da ? gradRasterDB.data_ptr<float>() : NULL;
+
+    // Verify that buffers are aligned to allow float2/float4 operations.
+    NVDR_CHECK(!((uintptr_t)p.rast         & 15), "rast input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.rastDB       & 15), "rast_db input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.dda          &  7), "dda input tensor not aligned to float2");
+    NVDR_CHECK(!((uintptr_t)p.gradRaster   & 15), "grad_rast output tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.gradRasterDB & 15), "grad_rast_db output tensor not aligned to float4");
+
+    // Choose launch parameters.
+    dim3 blockSize = getLaunchBlockSize(IP_GRAD_MAX_KERNEL_BLOCK_WIDTH, IP_GRAD_MAX_KERNEL_BLOCK_HEIGHT, p.width, p.height);
+    dim3 gridSize  = getLaunchGridSize(blockSize, p.width, p.height, p.depth);
+
+    // Launch CUDA kernel.
+    void* args[] = {&p};
+    void* func = enable_da ? (void*)InterpolateGradKernelDa : (void*)InterpolateGradKernel;
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel(func, gridSize, blockSize, args, 0, stream));
+
+    // Return results.
+    return std::tuple<torch::Tensor, torch::Tensor, torch::Tensor>(gradAttr, gradRaster, gradRasterDB);
+}
+
+// Version without derivatives.
+std::tuple<torch::Tensor, torch::Tensor> interpolate_grad(torch::Tensor attr, torch::Tensor rast, torch::Tensor tri, torch::Tensor dy)
+{
+    std::vector<int> empty_vec;
+    torch::Tensor empty_tensor;
+    std::tuple<torch::Tensor, torch::Tensor, torch::Tensor> result = interpolate_grad_da(attr, rast, tri, dy, empty_tensor, empty_tensor, false, empty_vec);
+    return std::tuple<torch::Tensor, torch::Tensor>(std::get<0>(result), std::get<1>(result));
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_rasterize.cpp b/extensions/nvdiffrast/nvdiffrast/torch/torch_rasterize.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..589e227ac0a8dc9735e32a3b77e38a5d1e11c882
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_rasterize.cpp
@@ -0,0 +1,265 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+#include "torch_types.h"
+#include "../common/common.h"
+#include "../common/rasterize.h"
+#include "../common/cudaraster/CudaRaster.hpp"
+#include "../common/cudaraster/impl/Constants.hpp"
+#include <tuple>
+
+//------------------------------------------------------------------------
+// Kernel prototypes.
+
+void RasterizeCudaFwdShaderKernel(const RasterizeCudaFwdShaderParams p);
+void RasterizeGradKernel(const RasterizeGradParams p);
+void RasterizeGradKernelDb(const RasterizeGradParams p);
+
+//------------------------------------------------------------------------
+// Python CudaRaster state wrapper methods.
+
+RasterizeCRStateWrapper::RasterizeCRStateWrapper(int cudaDeviceIdx_)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(cudaDeviceIdx_);
+    cudaDeviceIdx = cudaDeviceIdx_;
+    cr = new CR::CudaRaster();
+}
+
+RasterizeCRStateWrapper::~RasterizeCRStateWrapper(void)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(cudaDeviceIdx);
+    delete cr;
+}
+
+//------------------------------------------------------------------------
+// Forward op (Cuda).
+
+std::tuple<torch::Tensor, torch::Tensor> rasterize_fwd_cuda(RasterizeCRStateWrapper& stateWrapper, torch::Tensor pos, torch::Tensor tri, std::tuple<int, int> resolution, torch::Tensor ranges, int peeling_idx)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(pos));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    CR::CudaRaster* cr = stateWrapper.cr;
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(pos, tri);
+    NVDR_CHECK_CPU(ranges);
+    NVDR_CHECK_CONTIGUOUS(pos, tri, ranges);
+    NVDR_CHECK_F32(pos);
+    NVDR_CHECK_I32(tri, ranges);
+
+    // Check that CudaRaster context was created for the correct GPU.
+    NVDR_CHECK(pos.get_device() == stateWrapper.cudaDeviceIdx, "CudaRaster context must must reside on the same device as input tensors");
+
+    // Determine instance mode and check input dimensions.
+    bool instance_mode = pos.sizes().size() > 2;
+    if (instance_mode)
+        NVDR_CHECK(pos.sizes().size() == 3 && pos.size(0) > 0 && pos.size(1) > 0 && pos.size(2) == 4, "instance mode - pos must have shape [>0, >0, 4]");
+    else
+    {
+        NVDR_CHECK(pos.sizes().size() == 2 && pos.size(0) > 0 && pos.size(1) == 4, "range mode - pos must have shape [>0, 4]");
+        NVDR_CHECK(ranges.sizes().size() == 2 && ranges.size(0) > 0 && ranges.size(1) == 2, "range mode - ranges must have shape [>0, 2]");
+    }
+    NVDR_CHECK(tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+
+    // Get output shape.
+    int height_out = std::get<0>(resolution);
+    int width_out  = std::get<1>(resolution);
+    int depth      = instance_mode ? pos.size(0) : ranges.size(0); // Depth of tensor, not related to depth buffering.
+    NVDR_CHECK(height_out > 0 && width_out > 0, "resolution must be [>0, >0]");
+
+    // Round internal resolution up to tile size.
+    int height = (height_out + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+    int width  = (width_out  + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+
+    // Get position and triangle buffer sizes in vertices / triangles.
+    int posCount = instance_mode ? pos.size(1) : pos.size(0);
+    int triCount = tri.size(0);
+
+    // Set up CudaRaster buffers.
+    const float* posPtr = pos.data_ptr<float>();
+    const int32_t* rangesPtr = instance_mode ? 0 : ranges.data_ptr<int32_t>(); // This is in CPU memory.
+    const int32_t* triPtr = tri.data_ptr<int32_t>();
+    cr->setVertexBuffer((void*)posPtr, posCount);
+    cr->setIndexBuffer((void*)triPtr, triCount);
+    cr->setBufferSize(width_out, height_out, depth);
+
+    // Enable depth peeling?
+    bool enablePeel = (peeling_idx > 0);
+    cr->setRenderModeFlags(enablePeel ? CR::CudaRaster::RenderModeFlag_EnableDepthPeeling : 0); // No backface culling.
+    if (enablePeel)
+        cr->swapDepthAndPeel(); // Use previous depth buffer as peeling depth input.
+
+    // Determine viewport tiling.
+    int tileCountX = (width  + CR_MAXVIEWPORT_SIZE - 1) / CR_MAXVIEWPORT_SIZE;
+    int tileCountY = (height + CR_MAXVIEWPORT_SIZE - 1) / CR_MAXVIEWPORT_SIZE;
+    int tileSizeX = ((width  + tileCountX - 1) / tileCountX + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+    int tileSizeY = ((height + tileCountY - 1) / tileCountY + CR_TILE_SIZE - 1) & (-CR_TILE_SIZE);
+    TORCH_CHECK(tileCountX > 0 && tileCountY > 0 && tileSizeX > 0 && tileSizeY > 0,             "internal error in tile size calculation: count or size is zero");
+    TORCH_CHECK(tileSizeX <= CR_MAXVIEWPORT_SIZE && tileSizeY <= CR_MAXVIEWPORT_SIZE,           "internal error in tile size calculation: tile larger than allowed");
+    TORCH_CHECK((tileSizeX & (CR_TILE_SIZE - 1)) == 0 && (tileSizeY & (CR_TILE_SIZE - 1)) == 0, "internal error in tile size calculation: tile not divisible by ", CR_TILE_SIZE);
+    TORCH_CHECK(tileCountX * tileSizeX >= width && tileCountY * tileSizeY >= height,            "internal error in tile size calculation: tiles do not cover viewport");
+
+    // Rasterize in tiles.
+    for (int tileY = 0; tileY < tileCountY; tileY++)
+    for (int tileX = 0; tileX < tileCountX; tileX++)
+    {
+        // Set CudaRaster viewport according to tile.
+        int offsetX = tileX * tileSizeX;
+        int offsetY = tileY * tileSizeY;
+        int sizeX = (width_out  - offsetX) < tileSizeX ? (width_out  - offsetX) : tileSizeX;
+        int sizeY = (height_out - offsetY) < tileSizeY ? (height_out - offsetY) : tileSizeY;
+        cr->setViewport(sizeX, sizeY, offsetX, offsetY);
+
+        // Run all triangles in one batch. In case of error, the workload could be split into smaller batches - maybe do that in the future.
+        // Only enable peeling-specific optimizations to skip first stages when image fits in one tile. Those are not valid otherwise.
+        cr->deferredClear(0u);
+        bool success = cr->drawTriangles(rangesPtr, enablePeel && (tileCountX == 1 && tileCountY == 1), stream);
+        NVDR_CHECK(success, "subtriangle count overflow");
+    }
+
+    // Allocate output tensors.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
+    torch::Tensor out = torch::empty({depth, height_out, width_out, 4}, opts);
+    torch::Tensor out_db = torch::empty({depth, height_out, width_out, 4}, opts);
+
+    // Populate pixel shader kernel parameters.
+    RasterizeCudaFwdShaderParams p;
+    p.pos = posPtr;
+    p.tri = triPtr;
+    p.in_idx = (const int*)cr->getColorBuffer();
+    p.out = out.data_ptr<float>();
+    p.out_db = out_db.data_ptr<float>();
+    p.numTriangles = triCount;
+    p.numVertices = posCount;
+    p.width_in = width;
+    p.height_in = height;
+    p.width_out = width_out;
+    p.height_out = height_out;
+    p.depth  = depth;
+    p.instance_mode = (pos.sizes().size() > 2) ? 1 : 0;
+    p.xs = 2.f / (float)width_out;
+    p.xo = 1.f / (float)width_out - 1.f;
+    p.ys = 2.f / (float)height_out;
+    p.yo = 1.f / (float)height_out - 1.f;
+
+    // Verify that buffers are aligned to allow float2/float4 operations.
+    NVDR_CHECK(!((uintptr_t)p.pos & 15),    "pos input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.out & 15),    "out output tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.out_db & 15), "out_db output tensor not aligned to float4");
+
+    // Choose launch parameters.
+    dim3 blockSize = getLaunchBlockSize(RAST_CUDA_FWD_SHADER_KERNEL_BLOCK_WIDTH, RAST_CUDA_FWD_SHADER_KERNEL_BLOCK_HEIGHT, p.width_out, p.height_out);
+    dim3 gridSize  = getLaunchGridSize(blockSize, p.width_out, p.height_out, p.depth);
+
+    // Launch CUDA kernel.
+    void* args[] = {&p};
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel((void*)RasterizeCudaFwdShaderKernel, gridSize, blockSize, args, 0, stream));
+
+    // Return.
+    return std::tuple<torch::Tensor, torch::Tensor>(out, out_db);
+}
+
+//------------------------------------------------------------------------
+// Gradient op.
+
+torch::Tensor rasterize_grad_db(torch::Tensor pos, torch::Tensor tri, torch::Tensor out, torch::Tensor dy, torch::Tensor ddb)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(pos));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    RasterizeGradParams p;
+    bool enable_db = ddb.defined();
+
+    // Check inputs.
+    if (enable_db)
+    {
+        NVDR_CHECK_DEVICE(pos, tri, out, dy, ddb);
+        NVDR_CHECK_CONTIGUOUS(pos, tri, out);
+        NVDR_CHECK_F32(pos, out, dy, ddb);
+        NVDR_CHECK_I32(tri);
+    }
+    else
+    {
+        NVDR_CHECK_DEVICE(pos, tri, out, dy);
+        NVDR_CHECK_CONTIGUOUS(pos, tri, out);
+        NVDR_CHECK_F32(pos, out, dy);
+        NVDR_CHECK_I32(tri);
+    }
+
+    // Determine instance mode.
+    p.instance_mode = (pos.sizes().size() > 2) ? 1 : 0;
+
+    // Shape is taken from the rasterizer output tensor.
+    NVDR_CHECK(out.sizes().size() == 4, "tensor out must be rank-4");
+    p.depth  = out.size(0);
+    p.height = out.size(1);
+    p.width  = out.size(2);
+    NVDR_CHECK(p.depth > 0 && p.height > 0 && p.width > 0, "resolution must be [>0, >0, >0]");
+
+    // Check other shapes.
+    if (p.instance_mode)
+        NVDR_CHECK(pos.sizes().size() == 3 && pos.size(0) == p.depth && pos.size(1) > 0 && pos.size(2) == 4, "pos must have shape [depth, >0, 4]");
+    else
+        NVDR_CHECK(pos.sizes().size() == 2 && pos.size(0) > 0 && pos.size(1) == 4, "pos must have shape [>0, 4]");
+    NVDR_CHECK(tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+    NVDR_CHECK(out.sizes().size() == 4 && out.size(0) == p.depth && out.size(1) == p.height && out.size(2) == p.width && out.size(3) == 4, "out must have shape [depth, height, width, 4]");
+    NVDR_CHECK( dy.sizes().size() == 4 &&  dy.size(0) == p.depth &&  dy.size(1) == p.height &&  dy.size(2) == p.width &&  dy.size(3) == 4, "dy must have shape [depth, height, width, 4]");
+    if (enable_db)
+        NVDR_CHECK(ddb.sizes().size() == 4 && ddb.size(0) == p.depth && ddb.size(1) == p.height && ddb.size(2) == p.width && ddb.size(3) == 4, "ddb must have shape [depth, height, width, 4]");
+
+    // Ensure gradients are contiguous.
+    torch::Tensor dy_ = dy.contiguous();
+    torch::Tensor ddb_;
+    if (enable_db)
+        ddb_ = ddb.contiguous();
+
+    // Populate parameters.
+    p.numTriangles = tri.size(0);
+    p.numVertices = p.instance_mode ? pos.size(1) : pos.size(0);
+    p.pos = pos.data_ptr<float>();
+    p.tri = tri.data_ptr<int>();
+    p.out = out.data_ptr<float>();
+    p.dy  = dy_.data_ptr<float>();
+    p.ddb = enable_db ? ddb_.data_ptr<float>() : NULL;
+
+    // Set up pixel position to clip space x, y transform.
+    p.xs = 2.f / (float)p.width;
+    p.xo = 1.f / (float)p.width - 1.f;
+    p.ys = 2.f / (float)p.height;
+    p.yo = 1.f / (float)p.height - 1.f;
+
+    // Allocate output tensor for position gradients.
+    torch::Tensor grad = torch::zeros_like(pos);
+    p.grad = grad.data_ptr<float>();
+
+    // Verify that buffers are aligned to allow float2/float4 operations.
+    NVDR_CHECK(!((uintptr_t)p.pos & 15), "pos input tensor not aligned to float4");
+    NVDR_CHECK(!((uintptr_t)p.dy  &  7), "dy input tensor not aligned to float2");
+    NVDR_CHECK(!((uintptr_t)p.ddb & 15), "ddb input tensor not aligned to float4");
+
+    // Choose launch parameters.
+    dim3 blockSize = getLaunchBlockSize(RAST_GRAD_MAX_KERNEL_BLOCK_WIDTH, RAST_GRAD_MAX_KERNEL_BLOCK_HEIGHT, p.width, p.height);
+    dim3 gridSize  = getLaunchGridSize(blockSize, p.width, p.height, p.depth);
+
+    // Launch CUDA kernel.
+    void* args[] = {&p};
+    void* func = enable_db ? (void*)RasterizeGradKernelDb : (void*)RasterizeGradKernel;
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel(func, gridSize, blockSize, args, 0, stream));
+
+    // Return the gradients.
+    return grad;
+}
+
+// Version without derivatives.
+torch::Tensor rasterize_grad(torch::Tensor pos, torch::Tensor tri, torch::Tensor out, torch::Tensor dy)
+{
+    torch::Tensor empty_tensor;
+    return rasterize_grad_db(pos, tri, out, dy, empty_tensor);
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_rasterize_gl.cpp b/extensions/nvdiffrast/nvdiffrast/torch/torch_rasterize_gl.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..3776134adbd53f9138ef34fbbb2c00eb62883041
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_rasterize_gl.cpp
@@ -0,0 +1,132 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+#include "torch_types.h"
+#include "../common/common.h"
+#include "../common/rasterize_gl.h"
+#include <tuple>
+
+//------------------------------------------------------------------------
+// Python GL state wrapper methods.
+
+RasterizeGLStateWrapper::RasterizeGLStateWrapper(bool enableDB, bool automatic_, int cudaDeviceIdx_)
+{
+    pState = new RasterizeGLState();
+    automatic = automatic_;
+    cudaDeviceIdx = cudaDeviceIdx_;
+    memset(pState, 0, sizeof(RasterizeGLState));
+    pState->enableDB = enableDB ? 1 : 0;
+    rasterizeInitGLContext(NVDR_CTX_PARAMS, *pState, cudaDeviceIdx_);
+    releaseGLContext();
+}
+
+RasterizeGLStateWrapper::~RasterizeGLStateWrapper(void)
+{
+    setGLContext(pState->glctx);
+    rasterizeReleaseBuffers(NVDR_CTX_PARAMS, *pState);
+    releaseGLContext();
+    destroyGLContext(pState->glctx);
+    delete pState;
+}
+
+void RasterizeGLStateWrapper::setContext(void)
+{
+    setGLContext(pState->glctx);
+}
+
+void RasterizeGLStateWrapper::releaseContext(void)
+{
+    releaseGLContext();
+}
+
+//------------------------------------------------------------------------
+// Forward op (OpenGL).
+
+std::tuple<torch::Tensor, torch::Tensor> rasterize_fwd_gl(RasterizeGLStateWrapper& stateWrapper, torch::Tensor pos, torch::Tensor tri, std::tuple<int, int> resolution, torch::Tensor ranges, int peeling_idx)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(pos));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    RasterizeGLState& s = *stateWrapper.pState;
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(pos, tri);
+    NVDR_CHECK_CPU(ranges);
+    NVDR_CHECK_CONTIGUOUS(pos, tri, ranges);
+    NVDR_CHECK_F32(pos);
+    NVDR_CHECK_I32(tri, ranges);
+
+    // Check that GL context was created for the correct GPU.
+    NVDR_CHECK(pos.get_device() == stateWrapper.cudaDeviceIdx, "GL context must must reside on the same device as input tensors");
+
+    // Determine number of outputs
+    int num_outputs = s.enableDB ? 2 : 1;
+
+    // Determine instance mode and check input dimensions.
+    bool instance_mode = pos.sizes().size() > 2;
+    if (instance_mode)
+        NVDR_CHECK(pos.sizes().size() == 3 && pos.size(0) > 0 && pos.size(1) > 0 && pos.size(2) == 4, "instance mode - pos must have shape [>0, >0, 4]");
+    else
+    {
+        NVDR_CHECK(pos.sizes().size() == 2 && pos.size(0) > 0 && pos.size(1) == 4, "range mode - pos must have shape [>0, 4]");
+        NVDR_CHECK(ranges.sizes().size() == 2 && ranges.size(0) > 0 && ranges.size(1) == 2, "range mode - ranges must have shape [>0, 2]");
+    }
+    NVDR_CHECK(tri.sizes().size() == 2 && tri.size(0) > 0 && tri.size(1) == 3, "tri must have shape [>0, 3]");
+
+    // Get output shape.
+    int height = std::get<0>(resolution);
+    int width  = std::get<1>(resolution);
+    int depth  = instance_mode ? pos.size(0) : ranges.size(0);
+    NVDR_CHECK(height > 0 && width > 0, "resolution must be [>0, >0]");
+
+    // Get position and triangle buffer sizes in int32/float32.
+    int posCount = 4 * pos.size(0) * (instance_mode ? pos.size(1) : 1);
+    int triCount = 3 * tri.size(0);
+
+    // Set the GL context unless manual context.
+    if (stateWrapper.automatic)
+        setGLContext(s.glctx);
+
+    // Resize all buffers.
+    bool changes = false;
+    rasterizeResizeBuffers(NVDR_CTX_PARAMS, s, changes, posCount, triCount, width, height, depth);
+    if (changes)
+    {
+#ifdef _WIN32
+        // Workaround for occasional blank first frame on Windows.
+        releaseGLContext();
+        setGLContext(s.glctx);
+#endif
+    }
+
+    // Copy input data to GL and render.
+    const float* posPtr = pos.data_ptr<float>();
+    const int32_t* rangesPtr = instance_mode ? 0 : ranges.data_ptr<int32_t>(); // This is in CPU memory.
+    const int32_t* triPtr = tri.data_ptr<int32_t>();
+    int vtxPerInstance = instance_mode ? pos.size(1) : 0;
+    rasterizeRender(NVDR_CTX_PARAMS, s, stream, posPtr, posCount, vtxPerInstance, triPtr, triCount, rangesPtr, width, height, depth, peeling_idx);
+
+    // Allocate output tensors.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
+    torch::Tensor out = torch::empty({depth, height, width, 4}, opts);
+    torch::Tensor out_db = torch::empty({depth, height, width, s.enableDB ? 4 : 0}, opts);
+    float* outputPtr[2];
+    outputPtr[0] = out.data_ptr<float>();
+    outputPtr[1] = s.enableDB ? out_db.data_ptr<float>() : NULL;
+
+    // Copy rasterized results into CUDA buffers.
+    rasterizeCopyResults(NVDR_CTX_PARAMS, s, stream, outputPtr, width, height, depth);
+
+    // Done. Release GL context and return.
+    if (stateWrapper.automatic)
+        releaseGLContext();
+
+    return std::tuple<torch::Tensor, torch::Tensor>(out, out_db);
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_texture.cpp b/extensions/nvdiffrast/nvdiffrast/torch/torch_texture.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..2257f566623495c7044ea3f532ef00e327477dc7
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_texture.cpp
@@ -0,0 +1,718 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+#include "torch_types.h"
+#include "../common/common.h"
+#include "../common/texture.h"
+#include <cuda_runtime.h>
+
+//------------------------------------------------------------------------
+// Kernel prototypes.
+
+void MipBuildKernel1                            (const TextureKernelParams p);
+void MipBuildKernel2                            (const TextureKernelParams p);
+void MipBuildKernel4                            (const TextureKernelParams p);
+void TextureFwdKernelNearest1                   (const TextureKernelParams p);
+void TextureFwdKernelNearest2                   (const TextureKernelParams p);
+void TextureFwdKernelNearest4                   (const TextureKernelParams p);
+void TextureFwdKernelLinear1                    (const TextureKernelParams p);
+void TextureFwdKernelLinear2                    (const TextureKernelParams p);
+void TextureFwdKernelLinear4                    (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapNearest1       (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapNearest2       (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapNearest4       (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapLinear1        (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapLinear2        (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapLinear4        (const TextureKernelParams p);
+void TextureFwdKernelCubeNearest1               (const TextureKernelParams p);
+void TextureFwdKernelCubeNearest2               (const TextureKernelParams p);
+void TextureFwdKernelCubeNearest4               (const TextureKernelParams p);
+void TextureFwdKernelCubeLinear1                (const TextureKernelParams p);
+void TextureFwdKernelCubeLinear2                (const TextureKernelParams p);
+void TextureFwdKernelCubeLinear4                (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapNearest1   (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapNearest2   (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapNearest4   (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapLinear1    (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapLinear2    (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapLinear4    (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapNearestBO1     (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapNearestBO2     (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapNearestBO4     (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapLinearBO1      (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapLinearBO2      (const TextureKernelParams p);
+void TextureFwdKernelLinearMipmapLinearBO4      (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapNearestBO1 (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapNearestBO2 (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapNearestBO4 (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapLinearBO1  (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapLinearBO2  (const TextureKernelParams p);
+void TextureFwdKernelCubeLinearMipmapLinearBO4  (const TextureKernelParams p);
+void MipGradKernel1                             (const TextureKernelParams p);
+void MipGradKernel2                             (const TextureKernelParams p);
+void MipGradKernel4                             (const TextureKernelParams p);
+void TextureGradKernelNearest                   (const TextureKernelParams p);
+void TextureGradKernelLinear                    (const TextureKernelParams p);
+void TextureGradKernelLinearMipmapNearest       (const TextureKernelParams p);
+void TextureGradKernelLinearMipmapLinear        (const TextureKernelParams p);
+void TextureGradKernelCubeNearest               (const TextureKernelParams p);
+void TextureGradKernelCubeLinear                (const TextureKernelParams p);
+void TextureGradKernelCubeLinearMipmapNearest   (const TextureKernelParams p);
+void TextureGradKernelCubeLinearMipmapLinear    (const TextureKernelParams p);
+void TextureGradKernelLinearMipmapNearestBO     (const TextureKernelParams p);
+void TextureGradKernelLinearMipmapLinearBO      (const TextureKernelParams p);
+void TextureGradKernelCubeLinearMipmapNearestBO (const TextureKernelParams p);
+void TextureGradKernelCubeLinearMipmapLinearBO  (const TextureKernelParams p);
+
+//------------------------------------------------------------------------
+// Modeselektor.
+
+static void set_modes(TextureKernelParams& p, int filter_mode, int boundary_mode, int max_mip_level)
+{
+    // Mip and filter modes.
+    p.filterMode = filter_mode;
+    NVDR_CHECK(p.filterMode >= 0 && p.filterMode < TEX_MODE_COUNT, "filter_mode unsupported");
+    p.enableMip = (p.filterMode == TEX_MODE_LINEAR_MIPMAP_NEAREST || p.filterMode == TEX_MODE_LINEAR_MIPMAP_LINEAR);
+
+    // Mip level clamp.
+    if (p.enableMip)
+    {
+        p.mipLevelLimit = max_mip_level;
+        NVDR_CHECK(p.mipLevelLimit >= -1, "invalid max_mip_level");
+    }
+
+    // Boundary mode.
+    p.boundaryMode = boundary_mode;
+    NVDR_CHECK(p.boundaryMode >= 0 && p.boundaryMode < TEX_BOUNDARY_MODE_COUNT, "boundary_mode unsupported");
+}
+
+//------------------------------------------------------------------------
+// Mipmap construction.
+
+TextureMipWrapper texture_construct_mip(torch::Tensor tex, int max_mip_level, bool cube_mode)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(tex));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    TextureKernelParams p = {}; // Initialize all fields to zero.
+    p.mipLevelLimit = max_mip_level;
+    p.boundaryMode = cube_mode ? TEX_BOUNDARY_MODE_CUBE : TEX_BOUNDARY_MODE_WRAP;
+    NVDR_CHECK(p.mipLevelLimit >= -1, "invalid max_mip_level");
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(tex);
+    NVDR_CHECK_CONTIGUOUS(tex);
+    NVDR_CHECK_F32(tex);
+
+    // Populate parameters and sanity check tex shape.
+    if (!cube_mode)
+    {
+        NVDR_CHECK(tex.sizes().size() == 4 && tex.size(0) > 0 && tex.size(1) > 0 && tex.size(2) > 0 && tex.size(3) > 0, "tex must have shape[>0, >0, >0, >0]");
+    }
+    else
+    {
+        NVDR_CHECK(tex.sizes().size() == 5 && tex.size(0) > 0 && tex.size(1) == 6 && tex.size(2) > 0 && tex.size(3) > 0 && tex.size(4) > 0, "tex must have shape[>0, 6, >0, >0, >0] in cube map mode");
+        NVDR_CHECK(tex.size(2) == tex.size(3), "texture shape must be square in cube map mode");
+    }
+    p.texDepth  = tex.size(0);
+    p.texHeight = tex.size(cube_mode ? 2 : 1);
+    p.texWidth  = tex.size(cube_mode ? 3 : 2);
+    p.channels  = tex.size(cube_mode ? 4 : 3);
+
+    // Set texture pointer.
+    p.tex[0] = tex.data_ptr<float>();
+
+    // Generate mip offsets and calculate total size.
+    int mipOffsets[TEX_MAX_MIP_LEVEL];
+    int mipTotal = calculateMipInfo(NVDR_CTX_PARAMS, p, mipOffsets);
+
+    // Allocate and set mip tensor.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
+    torch::Tensor mip = torch::empty({mipTotal}, opts);
+    float* pmip = mip.data_ptr<float>();
+    for (int i=1; i <= p.mipLevelMax; i++)
+        p.tex[i] = pmip + mipOffsets[i]; // Pointers to mip levels.
+
+    // Choose kernel variants based on channel count.
+    void* args[] = {&p};
+    int channel_div_idx = 0;
+    if (!(p.channels & 3))
+        channel_div_idx = 2;  // Channel count divisible by 4.
+    else if (!(p.channels & 1))
+        channel_div_idx = 1;  // Channel count divisible by 2.
+
+    // Build mip levels.
+    for (int i=1; i <= p.mipLevelMax; i++)
+    {
+        int2 ms = mipLevelSize(p, i);
+        int3 sz = make_int3(ms.x, ms.y, p.texDepth);
+        dim3 blockSize = getLaunchBlockSize(TEX_FWD_MAX_MIP_KERNEL_BLOCK_WIDTH, TEX_FWD_MAX_MIP_KERNEL_BLOCK_HEIGHT, sz.x, sz.y);
+        dim3 gridSize  = getLaunchGridSize(blockSize, sz.x, sz.y, sz.z * (cube_mode ? 6 : 1));
+        p.mipLevelOut = i;
+
+        void* build_func_tbl[3] = { (void*)MipBuildKernel1, (void*)MipBuildKernel2, (void*)MipBuildKernel4 };
+        NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel(build_func_tbl[channel_div_idx], gridSize, blockSize, args, 0, stream));
+    }
+
+    // Return the mip tensor in a wrapper.
+    TextureMipWrapper mip_wrapper;
+    mip_wrapper.mip = mip;
+    mip_wrapper.max_mip_level = max_mip_level;
+    mip_wrapper.texture_size = tex.sizes().vec();
+    mip_wrapper.cube_mode = cube_mode;
+    return mip_wrapper;
+}
+
+//------------------------------------------------------------------------
+// Forward op.
+
+torch::Tensor texture_fwd_mip(torch::Tensor tex, torch::Tensor uv, torch::Tensor uv_da, torch::Tensor mip_level_bias, TextureMipWrapper mip_wrapper, std::vector<torch::Tensor> mip_stack, int filter_mode, int boundary_mode)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(tex));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    TextureKernelParams p = {}; // Initialize all fields to zero.
+    bool has_mip_stack = (mip_stack.size() > 0);
+    torch::Tensor& mip_w = mip_wrapper.mip; // Unwrap.
+    int max_mip_level = has_mip_stack ? mip_stack.size() : mip_wrapper.max_mip_level;
+    set_modes(p, filter_mode, boundary_mode, max_mip_level);
+
+    // See if we have these tensors or not.
+    bool has_uv_da = uv_da.defined() && uv_da.nbytes();
+    bool has_mip_level_bias = mip_level_bias.defined() && mip_level_bias.nbytes();
+
+    if (p.enableMip)
+    {
+        NVDR_CHECK(has_uv_da || has_mip_level_bias, "mipmapping filter mode requires uv_da and/or mip_level_bias input");
+        NVDR_CHECK(has_mip_stack || mip_w.defined(), "mipmapping filter mode requires mip wrapper or mip stack input");
+    }
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(tex, uv);
+    NVDR_CHECK_CONTIGUOUS(tex, uv);
+    NVDR_CHECK_F32(tex, uv);
+    if (p.enableMip)
+    {
+        if (has_mip_stack)
+        {
+            TORCH_CHECK(at::cuda::check_device(mip_stack), __func__, "(): Mip stack inputs must reside on the correct GPU device");
+            nvdr_check_contiguous(mip_stack, __func__, "(): Mip stack inputs must be contiguous tensors");
+            nvdr_check_f32(mip_stack, __func__, "(): Mip stack inputs must be float32 tensors");
+        }
+        else
+        {
+            NVDR_CHECK_DEVICE(mip_w);
+            NVDR_CHECK_CONTIGUOUS(mip_w);
+            NVDR_CHECK_F32(mip_w);
+        }
+        if (has_uv_da)
+        {
+            NVDR_CHECK_DEVICE(uv_da);
+            NVDR_CHECK_CONTIGUOUS(uv_da);
+            NVDR_CHECK_F32(uv_da);
+        }
+        if (has_mip_level_bias)
+        {
+            NVDR_CHECK_DEVICE(mip_level_bias);
+            NVDR_CHECK_CONTIGUOUS(mip_level_bias);
+            NVDR_CHECK_F32(mip_level_bias);
+        }
+    }
+
+    // Sanity checks and state setters.
+    bool cube_mode = (boundary_mode == TEX_BOUNDARY_MODE_CUBE);
+    if (!cube_mode)
+    {
+        NVDR_CHECK(tex.sizes().size() == 4 && tex.size(0) > 0 && tex.size(1) > 0 && tex.size(2) > 0 && tex.size(3) > 0, "tex must have shape[>0, >0, >0, >0]");
+        NVDR_CHECK(uv.sizes().size() == 4 && uv.size(0) > 0 && uv.size(1) > 0 && uv.size(2) > 0 && uv.size(3) == 2, "uv must have shape [>0, >0, >0, 2]");
+        p.texHeight = tex.size(1);
+        p.texWidth  = tex.size(2);
+        p.channels  = tex.size(3);
+    }
+    else
+    {
+        NVDR_CHECK(tex.sizes().size() == 5 && tex.size(0) > 0 && tex.size(1) == 6 && tex.size(2) > 0 && tex.size(3) > 0 && tex.size(4) > 0, "tex must have shape[>0, 6, >0, >0, >0] in cube map mode");
+        NVDR_CHECK(uv.sizes().size() == 4 && uv.size(0) > 0 && uv.size(1) > 0 && uv.size(2) > 0 && uv.size(3) == 3, "uv must have shape [>0, >0, >0, 3] in cube map mode");
+        NVDR_CHECK(tex.size(2) == tex.size(3), "texture shape must be square in cube map mode");
+        p.texHeight = tex.size(2);
+        p.texWidth  = tex.size(3);
+        p.channels  = tex.size(4);
+    }
+    NVDR_CHECK(tex.size(0) == 1 || tex.size(0) == uv.size(0), "minibatch size mismatch between inputs tex, uv");
+    NVDR_CHECK(p.texWidth <= (1 << TEX_MAX_MIP_LEVEL) && p.texHeight <= (1 << TEX_MAX_MIP_LEVEL), "texture size too large");
+    p.n         = uv.size(0);
+    p.imgHeight = uv.size(1);
+    p.imgWidth  = uv.size(2);
+    p.texDepth  = tex.size(0);
+    if (p.enableMip)
+    {
+        if (has_uv_da)
+        {
+            if (!cube_mode)
+                NVDR_CHECK(uv_da.sizes().size() == 4 && uv_da.size(0) == p.n && uv_da.size(1) == p.imgHeight && uv_da.size(2) == p.imgWidth && uv_da.size(3) == 4, "uv_da must have shape [minibatch_size, height, width, 4]");
+            else
+                NVDR_CHECK(uv_da.sizes().size() == 4 && uv_da.size(0) == p.n && uv_da.size(1) == p.imgHeight && uv_da.size(2) == p.imgWidth && uv_da.size(3) == 6, "uv_da must have shape [minibatch_size, height, width, 6] in cube map mode");
+        }
+        if (has_mip_level_bias)
+            NVDR_CHECK(mip_level_bias.sizes().size() == 3 && mip_level_bias.size(0) == p.n && mip_level_bias.size(1) == p.imgHeight && mip_level_bias.size(2) == p.imgWidth, "mip_level_bias must have shape [minibatch_size, height, width]");
+    }
+
+    // Get input pointers.
+    p.tex[0] = tex.data_ptr<float>();
+    p.uv = uv.data_ptr<float>();
+    p.uvDA = (p.enableMip && has_uv_da) ? uv_da.data_ptr<float>() : NULL;
+    p.mipLevelBias = (p.enableMip && has_mip_level_bias) ? mip_level_bias.data_ptr<float>() : NULL;
+
+    // Allocate output tensor.
+    torch::TensorOptions opts = torch::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA);
+    torch::Tensor out = torch::empty({p.n, p.imgHeight, p.imgWidth, p.channels}, opts);
+    p.out = out.data_ptr<float>();
+
+    // Choose kernel variants based on channel count.
+    void* args[] = {&p};
+    int channel_div_idx = 0;
+    if (!(p.channels & 3))
+        channel_div_idx = 2;  // Channel count divisible by 4.
+    else if (!(p.channels & 1))
+        channel_div_idx = 1;  // Channel count divisible by 2.
+
+    // Mip-related setup.
+    float* pmip = 0;
+    if (p.enableMip)
+    {
+        if (has_mip_stack)
+        {
+            // Custom mip stack supplied. Check that sizes match and assign.
+            p.mipLevelMax = max_mip_level;
+            for (int i=1; i <= p.mipLevelMax; i++)
+            {
+                torch::Tensor& t = mip_stack[i-1];
+                int2 sz = mipLevelSize(p, i);
+                if (!cube_mode)
+                    NVDR_CHECK(t.sizes().size() == 4 && t.size(0) == tex.size(0) && t.size(1) == sz.y && t.size(2) == sz.x && t.size(3) == p.channels, "mip level size mismatch in custom mip stack");
+                else
+                    NVDR_CHECK(t.sizes().size() == 5 && t.size(0) == tex.size(0) && t.size(1) == 6 && t.size(2) == sz.y && t.size(3) == sz.x && t.size(4) == p.channels, "mip level size mismatch in mip stack");
+                if (sz.x == 1 && sz.y == 1)
+                    NVDR_CHECK(i == p.mipLevelMax, "mip level size mismatch in mip stack");
+                p.tex[i] = t.data_ptr<float>();
+            }
+        }
+        else
+        {
+            // Generate mip offsets, check mipmap size, and set mip data pointer.
+            int mipOffsets[TEX_MAX_MIP_LEVEL];
+            int mipTotal = calculateMipInfo(NVDR_CTX_PARAMS, p, mipOffsets);
+            NVDR_CHECK(tex.sizes() == mip_wrapper.texture_size && cube_mode == mip_wrapper.cube_mode, "mip does not match texture size");
+            NVDR_CHECK(mip_w.sizes().size() == 1 && mip_w.size(0) == mipTotal, "wrapped mip tensor size mismatch");
+            pmip = mip_w.data_ptr<float>();
+            for (int i=1; i <= p.mipLevelMax; i++)
+                p.tex[i] = pmip + mipOffsets[i]; // Pointers to mip levels.
+        }
+    }
+
+    // Verify that buffers are aligned to allow float2/float4 operations. Unused pointers are zero so always aligned.
+    if (!cube_mode)
+        NVDR_CHECK(!((uintptr_t)p.uv & 7), "uv input tensor not aligned to float2");
+    if ((p.channels & 3) == 0)
+    {
+        for (int i=0; i <= p.mipLevelMax; i++)
+            NVDR_CHECK(!((uintptr_t)p.tex[i] & 15), "tex or mip input tensor not aligned to float4");
+        NVDR_CHECK(!((uintptr_t)p.out    & 15), "out output tensor not aligned to float4");
+        NVDR_CHECK(!((uintptr_t)pmip     & 15), "mip input tensor not aligned to float4");
+    }
+    if ((p.channels & 1) == 0)
+    {
+        for (int i=0; i <= p.mipLevelMax; i++)
+            NVDR_CHECK(!((uintptr_t)p.tex[i] & 7), "tex or mip input tensor not aligned to float2");
+        NVDR_CHECK(!((uintptr_t)p.out    & 7), "out output tensor not aligned to float2");
+        NVDR_CHECK(!((uintptr_t)pmip     & 7), "mip input tensor not aligned to float2");
+    }
+    if (!cube_mode)
+        NVDR_CHECK(!((uintptr_t)p.uvDA & 15), "uv_da input tensor not aligned to float4");
+    else
+        NVDR_CHECK(!((uintptr_t)p.uvDA & 7), "uv_da input tensor not aligned to float2");
+
+    // Choose launch parameters for texture lookup kernel.
+    dim3 blockSize = getLaunchBlockSize(TEX_FWD_MAX_KERNEL_BLOCK_WIDTH, TEX_FWD_MAX_KERNEL_BLOCK_HEIGHT, p.imgWidth, p.imgHeight);
+    dim3 gridSize  = getLaunchGridSize(blockSize, p.imgWidth, p.imgHeight, p.n);
+
+    // Choose kernel based on filter mode, cube mode, bias-only mode, and datatype.
+    void* func_tbl[TEX_MODE_COUNT * 2 * 2 * 3] = {
+        (void*)TextureFwdKernelNearest1,
+        (void*)TextureFwdKernelNearest2,
+        (void*)TextureFwdKernelNearest4,
+        (void*)TextureFwdKernelLinear1,
+        (void*)TextureFwdKernelLinear2,
+        (void*)TextureFwdKernelLinear4,
+        (void*)TextureFwdKernelLinearMipmapNearest1,
+        (void*)TextureFwdKernelLinearMipmapNearest2,
+        (void*)TextureFwdKernelLinearMipmapNearest4,
+        (void*)TextureFwdKernelLinearMipmapLinear1,
+        (void*)TextureFwdKernelLinearMipmapLinear2,
+        (void*)TextureFwdKernelLinearMipmapLinear4,
+        (void*)TextureFwdKernelCubeNearest1,
+        (void*)TextureFwdKernelCubeNearest2,
+        (void*)TextureFwdKernelCubeNearest4,
+        (void*)TextureFwdKernelCubeLinear1,
+        (void*)TextureFwdKernelCubeLinear2,
+        (void*)TextureFwdKernelCubeLinear4,
+        (void*)TextureFwdKernelCubeLinearMipmapNearest1,
+        (void*)TextureFwdKernelCubeLinearMipmapNearest2,
+        (void*)TextureFwdKernelCubeLinearMipmapNearest4,
+        (void*)TextureFwdKernelCubeLinearMipmapLinear1,
+        (void*)TextureFwdKernelCubeLinearMipmapLinear2,
+        (void*)TextureFwdKernelCubeLinearMipmapLinear4,
+        NULL,
+        NULL,
+        NULL,
+        NULL,
+        NULL,
+        NULL,
+        (void*)TextureFwdKernelLinearMipmapNearestBO1,
+        (void*)TextureFwdKernelLinearMipmapNearestBO2,
+        (void*)TextureFwdKernelLinearMipmapNearestBO4,
+        (void*)TextureFwdKernelLinearMipmapLinearBO1,
+        (void*)TextureFwdKernelLinearMipmapLinearBO2,
+        (void*)TextureFwdKernelLinearMipmapLinearBO4,
+        NULL,
+        NULL,
+        NULL,
+        NULL,
+        NULL,
+        NULL,
+        (void*)TextureFwdKernelCubeLinearMipmapNearestBO1,
+        (void*)TextureFwdKernelCubeLinearMipmapNearestBO2,
+        (void*)TextureFwdKernelCubeLinearMipmapNearestBO4,
+        (void*)TextureFwdKernelCubeLinearMipmapLinearBO1,
+        (void*)TextureFwdKernelCubeLinearMipmapLinearBO2,
+        (void*)TextureFwdKernelCubeLinearMipmapLinearBO4,
+    };
+
+    // Function index.
+    int func_idx = p.filterMode;
+    if (cube_mode)
+        func_idx += TEX_MODE_COUNT; // Cube variant.
+    if (p.enableMip && !has_uv_da)
+        func_idx += TEX_MODE_COUNT * 2; // Bias-only variant.
+    func_idx = func_idx * 3 + channel_div_idx; // Choose vector size.
+
+    // Launch kernel.
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel(func_tbl[func_idx], gridSize, blockSize, args, 0, stream));
+
+    // Return output tensor.
+    return out;
+}
+
+// Version without mipmaps.
+torch::Tensor texture_fwd(torch::Tensor tex, torch::Tensor uv, int filter_mode, int boundary_mode)
+{
+    torch::Tensor empty_tensor;
+    std::vector<torch::Tensor> empty_vector;
+    return texture_fwd_mip(tex, uv, empty_tensor, empty_tensor, TextureMipWrapper(), empty_vector, filter_mode, boundary_mode);
+}
+
+//------------------------------------------------------------------------
+// Gradient op.
+
+std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, std::vector<torch::Tensor> > texture_grad_linear_mipmap_linear(torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, torch::Tensor uv_da, torch::Tensor mip_level_bias, TextureMipWrapper mip_wrapper, std::vector<torch::Tensor> mip_stack, int filter_mode, int boundary_mode)
+{
+    const at::cuda::OptionalCUDAGuard device_guard(device_of(tex));
+    cudaStream_t stream = at::cuda::getCurrentCUDAStream();
+    TextureKernelParams p = {}; // Initialize all fields to zero.
+    bool has_mip_stack = (mip_stack.size() > 0);
+    torch::Tensor& mip_w = mip_wrapper.mip; // Unwrap.
+    int max_mip_level = has_mip_stack ? mip_stack.size() : mip_wrapper.max_mip_level;
+    set_modes(p, filter_mode, boundary_mode, max_mip_level);
+
+    // See if we have these tensors or not.
+    bool has_uv_da = uv_da.defined() && uv_da.nbytes();
+    bool has_mip_level_bias = mip_level_bias.defined() && mip_level_bias.nbytes();
+
+    if (p.enableMip)
+    {
+        NVDR_CHECK(has_uv_da || has_mip_level_bias, "mipmapping filter mode requires uv_da and/or mip_level_bias input");
+        NVDR_CHECK(has_mip_stack || mip_w.defined(), "mipmapping filter mode requires mip wrapper or mip stack input");
+    }
+
+    // Check inputs.
+    NVDR_CHECK_DEVICE(tex, uv);
+    NVDR_CHECK_CONTIGUOUS(tex, uv);
+    NVDR_CHECK_F32(tex, uv);
+    if (p.enableMip)
+    {
+        if (has_mip_stack)
+        {
+            TORCH_CHECK(at::cuda::check_device(mip_stack), __func__, "(): Mip stack inputs must reside on the correct GPU device");
+            nvdr_check_contiguous(mip_stack, __func__, "(): Mip stack inputs must be contiguous tensors");
+            nvdr_check_f32(mip_stack, __func__, "(): Mip stack inputs must be float32 tensors");
+        }
+        else
+        {
+            NVDR_CHECK_DEVICE(mip_w);
+            NVDR_CHECK_CONTIGUOUS(mip_w);
+            NVDR_CHECK_F32(mip_w);
+        }
+        if (has_uv_da)
+        {
+            NVDR_CHECK_DEVICE(uv_da);
+            NVDR_CHECK_CONTIGUOUS(uv_da);
+            NVDR_CHECK_F32(uv_da);
+        }
+        if (has_mip_level_bias)
+        {
+            NVDR_CHECK_DEVICE(mip_level_bias);
+            NVDR_CHECK_CONTIGUOUS(mip_level_bias);
+            NVDR_CHECK_F32(mip_level_bias);
+        }
+    }
+
+    // Sanity checks and state setters.
+    bool cube_mode = (boundary_mode == TEX_BOUNDARY_MODE_CUBE);
+    if (!cube_mode)
+    {
+        NVDR_CHECK(tex.sizes().size() == 4 && tex.size(0) > 0 && tex.size(1) > 0 && tex.size(2) > 0 && tex.size(3) > 0, "tex must have shape[>0, >0, >0, >0]");
+        NVDR_CHECK(uv.sizes().size() == 4 && uv.size(0) > 0 && uv.size(1) > 0 && uv.size(2) > 0 && uv.size(3) == 2, "uv must have shape [>0, >0, >0, 2]");
+        p.texHeight = tex.size(1);
+        p.texWidth  = tex.size(2);
+        p.channels  = tex.size(3);
+    }
+    else
+    {
+        NVDR_CHECK(tex.sizes().size() == 5 && tex.size(0) > 0 && tex.size(1) == 6 && tex.size(2) > 0 && tex.size(3) > 0 && tex.size(4) > 0, "tex must have shape[>0, 6, >0, >0, >0] in cube map mode");
+        NVDR_CHECK(uv.sizes().size() == 4 && uv.size(0) > 0 && uv.size(1) > 0 && uv.size(2) > 0 && uv.size(3) == 3, "uv must have shape [>0, >0, >0, 3] in cube map mode");
+        NVDR_CHECK(tex.size(2) == tex.size(3), "texture shape must be square in cube map mode");
+        p.texHeight = tex.size(2);
+        p.texWidth  = tex.size(3);
+        p.channels  = tex.size(4);
+    }
+    NVDR_CHECK(tex.size(0) == 1 || tex.size(0) == uv.size(0), "minibatch size mismatch between inputs tex, uv");
+    NVDR_CHECK(p.texWidth <= (1 << TEX_MAX_MIP_LEVEL) && p.texHeight <= (1 << TEX_MAX_MIP_LEVEL), "texture size too large");
+    p.n         = uv.size(0);
+    p.imgHeight = uv.size(1);
+    p.imgWidth  = uv.size(2);
+    p.texDepth  = tex.size(0);
+    if (p.enableMip)
+    {
+        if (has_uv_da)
+        {
+            if (!cube_mode)
+                NVDR_CHECK(uv_da.sizes().size() == 4 && uv_da.size(0) == p.n && uv_da.size(1) == p.imgHeight && uv_da.size(2) == p.imgWidth && uv_da.size(3) == 4, "uv_da must have shape [minibatch_size, height, width, 4]");
+            else
+                NVDR_CHECK(uv_da.sizes().size() == 4 && uv_da.size(0) == p.n && uv_da.size(1) == p.imgHeight && uv_da.size(2) == p.imgWidth && uv_da.size(3) == 6, "uv_da must have shape [minibatch_size, height, width, 6] in cube map mode");
+        }
+        if (has_mip_level_bias)
+            NVDR_CHECK(mip_level_bias.sizes().size() == 3 && mip_level_bias.size(0) == p.n && mip_level_bias.size(1) == p.imgHeight && mip_level_bias.size(2) == p.imgWidth, "mip_level_bias must have shape [minibatch_size, height, width]");
+    }
+    NVDR_CHECK(dy.sizes().size() == 4 && dy.size(0) == p.n && dy.size(1) == p.imgHeight && dy.size(2) == p.imgWidth && dy.size(3) == p.channels, "dy must have shape [minibatch_size, height, width, channels]");
+
+    // Get contiguous version of dy.
+    torch::Tensor dy_ = dy.contiguous();
+
+    // Get input pointers.
+    p.tex[0] = tex.data_ptr<float>();
+    p.uv = uv.data_ptr<float>();
+    p.dy = dy_.data_ptr<float>();
+    p.uvDA = (p.enableMip && has_uv_da) ? uv_da.data_ptr<float>() : NULL;
+    p.mipLevelBias = (p.enableMip && has_mip_level_bias) ? mip_level_bias.data_ptr<float>() : NULL;
+
+    // Allocate output tensor for tex gradient.
+    torch::Tensor grad_tex = torch::zeros_like(tex);
+    p.gradTex[0] = grad_tex.data_ptr<float>();
+
+    // Allocate output tensor for uv gradient.
+    torch::Tensor grad_uv;
+    torch::Tensor grad_uv_da;
+    torch::Tensor grad_mip_level_bias;
+    if (p.filterMode != TEX_MODE_NEAREST)
+    {
+        grad_uv = torch::empty_like(uv);
+        p.gradUV = grad_uv.data_ptr<float>();
+
+        // Gradients for things affecting mip level.
+        if (p.filterMode == TEX_MODE_LINEAR_MIPMAP_LINEAR)
+        {
+            // Allocate output tensor for uv_da gradient.
+            if (has_uv_da)
+            {
+                grad_uv_da = torch::empty_like(uv_da);
+                p.gradUVDA = grad_uv_da.data_ptr<float>();
+            }
+
+            // Allocate output tensor for mip_level_bias gradient.
+            if (has_mip_level_bias)
+            {
+                grad_mip_level_bias = torch::empty_like(mip_level_bias);
+                p.gradMipLevelBias = grad_mip_level_bias.data_ptr<float>();
+            }
+        }
+    }
+
+    // Choose kernel variants based on channel count.
+    int channel_div_idx = 0;
+    if (!(p.channels & 3))
+        channel_div_idx = 2;  // Channel count divisible by 4.
+    else if (!(p.channels & 1))
+        channel_div_idx = 1;  // Channel count divisible by 2.
+
+    // Mip-related setup.
+    torch::Tensor grad_mip;
+    std::vector<torch::Tensor> grad_mip_stack;
+    float* pmip = 0;
+    float* pgradMip = 0;
+    if (p.enableMip)
+    {
+        if (has_mip_stack)
+        {
+            // Custom mip stack supplied. Check that sizes match, assign, construct gradient tensors.
+            p.mipLevelMax = max_mip_level;
+            for (int i=1; i <= p.mipLevelMax; i++)
+            {
+                torch::Tensor& t = mip_stack[i-1];
+                int2 sz = mipLevelSize(p, i);
+                if (!cube_mode)
+                    NVDR_CHECK(t.sizes().size() == 4 && t.size(0) == tex.size(0) && t.size(1) == sz.y && t.size(2) == sz.x && t.size(3) == p.channels, "mip level size mismatch in mip stack");
+                else
+                    NVDR_CHECK(t.sizes().size() == 5 && t.size(0) == tex.size(0) && t.size(1) == 6 && t.size(2) == sz.y && t.size(3) == sz.x && t.size(4) == p.channels, "mip level size mismatch in mip stack");
+                if (sz.x == 1 && sz.y == 1)
+                    NVDR_CHECK(i == p.mipLevelMax, "mip level size mismatch in mip stack");
+
+                torch::Tensor g = torch::zeros_like(t);
+                grad_mip_stack.push_back(g);
+
+                p.tex[i] = t.data_ptr<float>();
+                p.gradTex[i] = g.data_ptr<float>();
+            }
+        }
+        else
+        {
+            // Generate mip offsets and get space for temporary mip gradients.
+            int mipOffsets[TEX_MAX_MIP_LEVEL];
+            int mipTotal = calculateMipInfo(NVDR_CTX_PARAMS, p, mipOffsets);
+            NVDR_CHECK(tex.sizes() == mip_wrapper.texture_size && cube_mode == mip_wrapper.cube_mode, "mip does not match texture size");
+            NVDR_CHECK(mip_w.sizes().size() == 1 && mip_w.size(0) == mipTotal, "mip tensor size mismatch");
+            grad_mip = torch::zeros_like(mip_w);
+            pmip = (float*)mip_w.data_ptr<float>();
+            pgradMip = grad_mip.data_ptr<float>();
+            for (int i=1; i <= p.mipLevelMax; i++)
+            {
+                p.tex[i] = pmip + mipOffsets[i]; // Pointers to mip levels.
+                p.gradTex[i] = pgradMip + mipOffsets[i]; // Pointers to mip gradients.
+            }
+        }
+    }
+
+    // Verify that buffers are aligned to allow float2/float4 operations. Unused pointers are zero so always aligned.
+    if (!cube_mode)
+    {
+        NVDR_CHECK(!((uintptr_t)p.uv       & 7), "uv input tensor not aligned to float2");
+        NVDR_CHECK(!((uintptr_t)p.gradUV   & 7), "grad_uv output tensor not aligned to float2");
+        NVDR_CHECK(!((uintptr_t)p.uvDA     & 15), "uv_da input tensor not aligned to float4");
+        NVDR_CHECK(!((uintptr_t)p.gradUVDA & 15), "grad_uv_da output tensor not aligned to float4");
+    }
+    else
+    {
+        NVDR_CHECK(!((uintptr_t)p.uvDA     & 7), "uv_da input tensor not aligned to float2");
+        NVDR_CHECK(!((uintptr_t)p.gradUVDA & 7), "grad_uv_da output tensor not aligned to float2");
+    }
+    if ((p.channels & 3) == 0)
+    {
+        for (int i=0; i <= p.mipLevelMax; i++)
+        {
+            NVDR_CHECK(!((uintptr_t)p.tex[i]     & 15), "tex or mip input tensor not aligned to float4");
+            NVDR_CHECK(!((uintptr_t)p.gradTex[i] & 15), "grad_tex output tensor not aligned to float4");
+        }
+        NVDR_CHECK(!((uintptr_t)p.dy         & 15), "dy input tensor not aligned to float4");
+        NVDR_CHECK(!((uintptr_t)pmip         & 15), "mip input tensor not aligned to float4");
+        NVDR_CHECK(!((uintptr_t)pgradMip     & 15), "internal mip gradient tensor not aligned to float4");
+    }
+    if ((p.channels & 1) == 0)
+    {
+        for (int i=0; i <= p.mipLevelMax; i++)
+        {
+            NVDR_CHECK(!((uintptr_t)p.tex[i]     & 7), "tex or mip input tensor not aligned to float2");
+            NVDR_CHECK(!((uintptr_t)p.gradTex[i] & 7), "grad_tex output tensor not aligned to float2");
+        }
+         NVDR_CHECK(!((uintptr_t)p.dy         & 7), "dy output tensor not aligned to float2");
+        NVDR_CHECK(!((uintptr_t)pmip         & 7), "mip input tensor not aligned to float2");
+        NVDR_CHECK(!((uintptr_t)pgradMip     & 7), "internal mip gradient tensor not aligned to float2");
+    }
+
+    // Choose launch parameters for main gradient kernel.
+    void* args[] = {&p};
+    dim3 blockSize = getLaunchBlockSize(TEX_GRAD_MAX_KERNEL_BLOCK_WIDTH, TEX_GRAD_MAX_KERNEL_BLOCK_HEIGHT, p.imgWidth, p.imgHeight);
+    dim3 gridSize  = getLaunchGridSize(blockSize, p.imgWidth, p.imgHeight, p.n);
+
+    void* func_tbl[TEX_MODE_COUNT * 2 * 2] = {
+        (void*)TextureGradKernelNearest,
+        (void*)TextureGradKernelLinear,
+        (void*)TextureGradKernelLinearMipmapNearest,
+        (void*)TextureGradKernelLinearMipmapLinear,
+        (void*)TextureGradKernelCubeNearest,
+        (void*)TextureGradKernelCubeLinear,
+        (void*)TextureGradKernelCubeLinearMipmapNearest,
+        (void*)TextureGradKernelCubeLinearMipmapLinear,
+        NULL,
+        NULL,
+        (void*)TextureGradKernelLinearMipmapNearestBO,
+        (void*)TextureGradKernelLinearMipmapLinearBO,
+        NULL,
+        NULL,
+        (void*)TextureGradKernelCubeLinearMipmapNearestBO,
+        (void*)TextureGradKernelCubeLinearMipmapLinearBO,
+    };
+
+    // Function index.
+    int func_idx = p.filterMode;
+    if (cube_mode)
+        func_idx += TEX_MODE_COUNT; // Cube variant.
+    if (p.enableMip && !has_uv_da)
+        func_idx += TEX_MODE_COUNT * 2; // Bias-only variant.
+
+    // Launch main gradient kernel.
+    NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel(func_tbl[func_idx], gridSize, blockSize, args, 0, stream));
+
+    // Launch kernel to pull gradients from mip levels. Don't do this if mip stack was supplied - individual level gradients are already there.
+    if (p.enableMip && !has_mip_stack)
+    {
+        dim3 blockSize = getLaunchBlockSize(TEX_GRAD_MAX_MIP_KERNEL_BLOCK_WIDTH, TEX_GRAD_MAX_MIP_KERNEL_BLOCK_HEIGHT, p.texWidth, p.texHeight);
+        dim3 gridSize  = getLaunchGridSize(blockSize, p.texWidth, p.texHeight, p.texDepth * (cube_mode ? 6 : 1));
+        int sharedBytes = blockSize.x * blockSize.y * p.channels * sizeof(float);
+
+        void* mip_grad_func_tbl[3] = { (void*)MipGradKernel1, (void*)MipGradKernel2, (void*)MipGradKernel4 };
+        NVDR_CHECK_CUDA_ERROR(cudaLaunchKernel(mip_grad_func_tbl[channel_div_idx], gridSize, blockSize, args, sharedBytes, stream));
+    }
+
+    // Return output tensors.
+    return std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, std::vector<torch::Tensor> >(grad_tex, grad_uv, grad_uv_da, grad_mip_level_bias, grad_mip_stack);
+}
+
+// Version for nearest filter mode.
+torch::Tensor texture_grad_nearest(torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, int filter_mode, int boundary_mode)
+{
+    torch::Tensor empty_tensor;
+    std::vector<torch::Tensor> empty_vector;
+    std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, std::vector<torch::Tensor> > result = texture_grad_linear_mipmap_linear(tex, uv, dy, empty_tensor, empty_tensor, TextureMipWrapper(), empty_vector, filter_mode, boundary_mode);
+    return std::get<0>(result);
+}
+
+// Version for linear filter mode.
+std::tuple<torch::Tensor, torch::Tensor> texture_grad_linear(torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, int filter_mode, int boundary_mode)
+{
+    torch::Tensor empty_tensor;
+    std::vector<torch::Tensor> empty_vector;
+    std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, std::vector<torch::Tensor> > result = texture_grad_linear_mipmap_linear(tex, uv, dy, empty_tensor, empty_tensor, TextureMipWrapper(), empty_vector, filter_mode, boundary_mode);
+    return std::tuple<torch::Tensor, torch::Tensor>(std::get<0>(result), std::get<1>(result));
+}
+
+// Version for linear-mipmap-nearest mode.
+std::tuple<torch::Tensor, torch::Tensor, std::vector<torch::Tensor> > texture_grad_linear_mipmap_nearest(torch::Tensor tex, torch::Tensor uv, torch::Tensor dy, torch::Tensor uv_da, torch::Tensor mip_level_bias, TextureMipWrapper mip_wrapper, std::vector<torch::Tensor> mip_stack, int filter_mode, int boundary_mode)
+{
+    std::tuple<torch::Tensor, torch::Tensor, torch::Tensor, torch::Tensor, std::vector<torch::Tensor> > result = texture_grad_linear_mipmap_linear(tex, uv, dy, uv_da, mip_level_bias, mip_wrapper, mip_stack, filter_mode, boundary_mode);
+    return std::tuple<torch::Tensor, torch::Tensor, std::vector<torch::Tensor> >(std::get<0>(result), std::get<1>(result), std::get<4>(result));
+}
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/nvdiffrast/torch/torch_types.h b/extensions/nvdiffrast/nvdiffrast/torch/torch_types.h
new file mode 100644
index 0000000000000000000000000000000000000000..8e389582e65d5df91f4273b8959969fa6dbe1b37
--- /dev/null
+++ b/extensions/nvdiffrast/nvdiffrast/torch/torch_types.h
@@ -0,0 +1,65 @@
+// Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+//
+// NVIDIA CORPORATION and its licensors retain all intellectual property
+// and proprietary rights in and to this software, related documentation
+// and any modifications thereto.  Any use, reproduction, disclosure or
+// distribution of this software and related documentation without an express
+// license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+#include "torch_common.inl"
+
+//------------------------------------------------------------------------
+// Python GL state wrapper.
+
+class RasterizeGLState;
+class RasterizeGLStateWrapper
+{
+public:
+    RasterizeGLStateWrapper     (bool enableDB, bool automatic, int cudaDeviceIdx);
+    ~RasterizeGLStateWrapper    (void);
+
+    void setContext             (void);
+    void releaseContext         (void);
+
+    RasterizeGLState*           pState;
+    bool                        automatic;
+    int                         cudaDeviceIdx;
+};
+
+//------------------------------------------------------------------------
+// Python CudaRaster state wrapper.
+
+namespace CR { class CudaRaster; }
+class RasterizeCRStateWrapper
+{
+public:
+    RasterizeCRStateWrapper     (int cudaDeviceIdx);
+    ~RasterizeCRStateWrapper    (void);
+
+    CR::CudaRaster*             cr;
+    int                         cudaDeviceIdx;
+};
+
+//------------------------------------------------------------------------
+// Mipmap wrapper to prevent intrusion from Python side.
+
+class TextureMipWrapper
+{
+public:
+    torch::Tensor               mip;
+    int                         max_mip_level;
+    std::vector<int64_t>        texture_size;   // For error checking.
+    bool                        cube_mode;      // For error checking.
+};
+
+
+//------------------------------------------------------------------------
+// Antialias topology hash wrapper to prevent intrusion from Python side.
+
+class TopologyHashWrapper
+{
+public:
+    torch::Tensor               ev_hash;
+};
+
+//------------------------------------------------------------------------
diff --git a/extensions/nvdiffrast/run_sample.sh b/extensions/nvdiffrast/run_sample.sh
new file mode 100644
index 0000000000000000000000000000000000000000..3758865c3359c12da203fb34360f8caa2824e8ef
--- /dev/null
+++ b/extensions/nvdiffrast/run_sample.sh
@@ -0,0 +1,52 @@
+#!/bin/bash
+
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+function print_help {
+    echo "Usage: `basename $0` [--build-container] <python_file>"
+    echo ""
+    echo "Option --build-container will build the Docker container based on"
+    echo "docker/Dockerfile and tag the image with gltorch:latest."
+    echo ""
+    echo "Example: `basename $0` samples/torch/envphong.py"
+}
+
+build_container=0
+sample=""
+while [[ "$#" -gt 0 ]]; do
+    case $1 in
+        --build-container) build_container=1;;
+        -h|--help) print_help; exit 0 ;;
+        --*) echo "Unknown parameter passed: $1"; exit 1 ;;
+        *) sample="$1"; shift; break;
+    esac
+    shift
+done
+
+rest=$@
+
+# Build the docker container
+if [ "$build_container" = "1" ]; then
+    docker build --tag gltorch:latest -f docker/Dockerfile .
+fi
+
+if [ ! -f "$sample" ]; then
+    echo
+    echo "No python sample given or file '$sample' not found.  Exiting."
+    exit 1
+fi
+
+image="gltorch:latest"
+
+echo "Using container image: $image"
+echo "Running command: $sample $rest"
+
+# Run a sample with docker
+docker run --rm -it --gpus all --user $(id -u):$(id -g) \
+    -v `pwd`:/app --workdir /app -e TORCH_EXTENSIONS_DIR=/app/tmp $image python3 $sample $rest
diff --git a/extensions/nvdiffrast/setup copy.py b/extensions/nvdiffrast/setup copy.py
new file mode 100644
index 0000000000000000000000000000000000000000..f7f9dede9649583be8fdd2ba6aa6c3aab184ed54
--- /dev/null
+++ b/extensions/nvdiffrast/setup copy.py	
@@ -0,0 +1,51 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+import nvdiffrast
+import setuptools
+import os
+
+with open("README.md", "r") as fh:
+    long_description = fh.read()
+
+setuptools.setup(
+    name="nvdiffrast",
+    version=nvdiffrast.__version__,
+    author="Samuli Laine",
+    author_email="slaine@nvidia.com",
+    description="nvdiffrast - modular primitives for high-performance differentiable rendering",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    url="https://github.com/NVlabs/nvdiffrast",
+    packages=setuptools.find_packages(),
+    package_data={
+        'nvdiffrast': [
+            'common/*.h',
+            'common/*.inl',
+            'common/*.cu',
+            'common/*.cpp',
+            'common/cudaraster/*.hpp',
+            'common/cudaraster/impl/*.cpp',
+            'common/cudaraster/impl/*.hpp',
+            'common/cudaraster/impl/*.inl',
+            'common/cudaraster/impl/*.cu',
+            'lib/*.h',
+            'torch/*.h',
+            'torch/*.inl',
+            'torch/*.cpp',
+            'tensorflow/*.cu',
+        ] + (['lib/*.lib'] if os.name == 'nt' else [])
+    },
+    include_package_data=True,
+    install_requires=['numpy'],  # note: can't require torch here as it will install torch even for a TensorFlow container
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "Operating System :: OS Independent",
+    ],
+    python_requires='>=3.6',
+)
diff --git a/extensions/nvdiffrast/setup.py b/extensions/nvdiffrast/setup.py
new file mode 100644
index 0000000000000000000000000000000000000000..507cb06f18fbc948e81fd7791f87489d8c35347b
--- /dev/null
+++ b/extensions/nvdiffrast/setup.py
@@ -0,0 +1,82 @@
+# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
+#
+# NVIDIA CORPORATION and its licensors retain all intellectual property
+# and proprietary rights in and to this software, related documentation
+# and any modifications thereto.  Any use, reproduction, disclosure or
+# distribution of this software and related documentation without an express
+# license agreement from NVIDIA CORPORATION is strictly prohibited.
+
+import nvdiffrast
+import setuptools
+import os
+from torch.utils.cpp_extension import CUDAExtension, BuildExtension
+
+
+with open("README.md", "r") as fh:
+    long_description = fh.read()
+
+setuptools.setup(
+    name="nvdiffrast",
+    version=nvdiffrast.__version__,
+    author="Samuli Laine",
+    author_email="slaine@nvidia.com",
+    description="nvdiffrast - modular primitives for high-performance differentiable rendering",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    url="https://github.com/NVlabs/nvdiffrast",
+    packages=setuptools.find_packages(),
+    # package_data={
+    #     'nvdiffrast': [
+    #         'common/*.h',
+    #         'common/*.inl',
+    #         'common/*.cu',
+    #         'common/*.cpp',
+    #         'common/cudaraster/*.hpp',
+    #         'common/cudaraster/impl/*.cpp',
+    #         'common/cudaraster/impl/*.hpp',
+    #         'common/cudaraster/impl/*.inl',
+    #         'common/cudaraster/impl/*.cu',
+    #         'lib/*.h',
+    #         'torch/*.h',
+    #         'torch/*.inl',
+    #         'torch/*.cpp',
+    #         'tensorflow/*.cu',
+    #     ] + (['lib/*.lib'] if os.name == 'nt' else [])
+    # },
+    # include_package_data=True,
+    ext_modules=[
+        CUDAExtension(
+            name="nvdiffrast.torch._C",
+            sources=[
+                'nvdiffrast/common/cudaraster/impl/Buffer.cpp',
+                'nvdiffrast/common/cudaraster/impl/CudaRaster.cpp',
+                'nvdiffrast/common/cudaraster/impl/RasterImpl_.cu',
+                'nvdiffrast/common/cudaraster/impl/RasterImpl.cpp',
+                'nvdiffrast/common/common.cpp',
+                'nvdiffrast/common/rasterize.cu',
+                'nvdiffrast/common/interpolate.cu',
+                'nvdiffrast/common/texture_.cu',
+                'nvdiffrast/common/texture.cpp',
+                'nvdiffrast/common/antialias.cu',
+                'nvdiffrast/torch/torch_bindings.cpp',
+                'nvdiffrast/torch/torch_rasterize.cpp',
+                'nvdiffrast/torch/torch_interpolate.cpp',
+                'nvdiffrast/torch/torch_texture.cpp',
+                'nvdiffrast/torch/torch_antialias.cpp',
+            ],
+            extra_compile_args={
+                'cxx': ['-DNVDR_TORCH'],
+                'nvcc': ['-DNVDR_TORCH', '-lineinfo'],
+            },
+        )
+    ],
+    cmdclass={
+        'build_ext': BuildExtension
+    },
+    install_requires=['numpy'],  # note: can't require torch here as it will install torch even for a TensorFlow container
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "Operating System :: OS Independent",
+    ],
+    python_requires='>=3.6',
+)
diff --git a/requirements.txt b/requirements.txt
index 43749293a1360713205401f522ba3a0dd3095850..7f4e65025cf51feb4e5911db7491cfef0d0a8967 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -25,4 +25,4 @@ transformers==4.46.3
 gradio_litmodel3d==0.0.1
 https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.0.post2/flash_attn-2.7.0.post2+cu12torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
 https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
-https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/nvdiffrast-0.3.3-py3-none-any.whl?download=true
\ No newline at end of file
+https://huggingface.co/spaces/JeffreyXiang/TRELLIS/resolve/main/wheels/nvdiffrast-0.3.3-cp310-cp310-linux_x86_64.whl?download=true
\ No newline at end of file
diff --git a/wheels/nvdiffrast-0.3.3-py3-none-any.whl b/wheels/nvdiffrast-0.3.3-py3-none-any.whl
deleted file mode 100644
index cb56d6d359394e2829cd6a433f6f938a49ee733f..0000000000000000000000000000000000000000
Binary files a/wheels/nvdiffrast-0.3.3-py3-none-any.whl and /dev/null differ