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The same 71-block Swin / ViT network as DLSS-NR build 310.8.0, running FP8 on the tensor cores. The
intermediates match too, not just the final image: all 75 block boundaries, byte for byte. ports/browser-webgpu/ is a second, independent implementation: the same bytes in a browser, with no
tensor cores and no FP8. You supply the weights , as a model directory in the layout described below. The network (OpenDLSS-NR.html#the-network)     A U-net of shifted-window transformer blocks with a global ViT at the bottom: 71 blocks over six pooling
levels, FP8 (E4M3) activations with FP16 accumulation, 141 MiB of weights. It is a generative neural rendering
network (NVIDIA's term): it re-renders the frame the engine already drew, generating detail from injected noise
and adjusting tone, structure and skin under a style setting. Input and output are the same resolution; it is not
an upscaler. (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/images/cowboy-gramps-nr-on.jpg) (The same frame with neural rendering off (left) and on (right))   The WebGPU port at 2048x1152, NR off on the left and on on the right. Scene: (https://www.blendkit.com/asset-gallery-detail/96dce188-9c9c-4699-a45a-48663fbbbcb7/) Cowboy Gramps by
Muhammed Ismayil, CC0.  It takes one rendered frame (a low dynamic range proxy of it, three lanes of Gaussian noise, the previous
frame's output reprojected, and five conditioning scalars) and produces four f32 channels per pixel: an RGB
residual and one temporal-blend logit. (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/network.md) docs/network.md is the graph in full. NVIDIA
describes the model in its report, (https://research.nvidia.com/labs/adlr/DLSS5/files/DLSS5_Report.pdf) DLSS 5: Generative Neural Rendering ((https://research.nvidia.com/labs/adlr/DLSS5/) project page ). Build and run (OpenDLSS-NR.html#build-and-run)     powershell -File scripts\fetch_tools.ps1 [-Npm]     # once: tools\ (glslang, Vulkan-Headers, volk, CMake, Ninja)
powershell -File scripts\build.ps1                  # shaders, PTX, build\dlss5vk.exe
powershell -File scripts\fetch_filament.ps1         # once, for the demo: third_party\filament (+ the patch)
powershell -File scripts\build_filament.ps1         # once, for the demo: third_party\filament-install
powershell -File scripts\build_demo.ps1             # build\demo\dlss5-demo.exe    build\dlss5vk.exe bench   --model <dir> --width 768 --height 768
build\dlss5vk.exe profile --model <dir> --width 768 --height 768   # per-dispatch timings
build\dlss5vk.exe parity  --model <dir> --fixture <dir>            # bit-exactness against a fixture
build\dlss5vk.exe verify  --model <dir> --fixture <dir>            # block-0 kernel-by-kernel bisect
python scripts\ptx\test_fast_divmod.py                             # the PTX divider, over every n < 2^24 (numpy)    The demo can be double-clicked. It lists every scene under build\scenes in the Demo scene dropdown and
starts on the first one, or loads the glTF given on the command line. The model directory is --model <dir> ,
else DLSS5VK_MODEL , else models\nr next to this README. See (https://github.com/maanHimself/OpenDLSS-NR/blob/main/demo/README.md) demo/README.md for the
renderer, the keys, the scenes and view.json . Performance (OpenDLSS-NR.html#performance)     RTX 4070 SUPER, whole network per frame, minimum over 40 frames. 241 dispatches at every resolution. resolution time   768x768 2.8 ms  1920x1080 7.8 ms  2560x1440 12.6 ms  3840x2160 29.3 ms     The GPU alternates between two clock states under sustained load, so medians run a few percent higher. Compare
minima. What is here (OpenDLSS-NR.html#what-is-here)     Part Files Notes   Host src/ (C++20) Vulkan context, model loading and weight re-layout, kernel wrappers, the network graph, a CPU reference of the arithmetic, the dlss5vk tool  GLSL kernels shaders/  The reference route: cooperative-matrix FP8 GEMMs, fused 32-channel block, fused QKV + window attention, expert MLP, global attention, elementwise ops. Exact and complete on their own.  PTX kernels scripts/ptx/  Python generators emitting PTX for the fast route: mma.sync E4M3 with f16 accumulation, cp.async rings, barrier-free chaining through device counters, split-K GEMMs, streamed global attention. Generated into build/ptx by the build.  Demo demo/ , third_party/filament.patch  The network inside a Filament (Apache-2.0) frame: Filament patched for per-object motion vectors and a Vulkan interop hook, glTF scenes through gltfio, ImGui controls.  WebGPU port ports/browser-webgpu/  The same network in a browser, bit-exact against the same captures, with no tensor core, no FP8, no fusion between blocks and no chaining: the exactness is in the specification, not in the hardware. 72 ms at 512x512 against 2.7 ms here.     Not implemented: DLSS-SR, which is a different network. The temporal path is implemented, but in the demo: the
network's history input lanes and its per-pixel blend logit drive a reprojected feedback loop
((https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/frame.md) docs/frame.md ). The dlss5vk tool runs single frames with no history, which is what the
reference captures were made with. Requirements (OpenDLSS-NR.html#requirements)     Windows, an NVIDIA Ada (or newer) GPU and a driver exposing VK_KHR_cooperative_matrix , VK_NV_cooperative_matrix2 , VK_EXT_shader_float8 and VK_NV_cuda_kernel_launch . Visual Studio 2022 or later with the C++ x64 toolset (any edition or the Build Tools; found through vswhere,
or set VCVARS64 to your vcvars64.bat ), git, Python 3 for the PTX generators, and Node.js + npm and
Pillow for the scene converter. The portable toolchain under tools/ (git-ignored): scripts\fetch_tools.ps1 downloads glslang 16.6.0,
Vulkan-Headers v1.4.363, volk (pinned tags), CMake 3.31 and Ninja 1.13. No Vulkan SDK install is needed. -Npm also installs the scene converter's modules into tools\gltf . For the demo: Filament v1.77.0, cloned and patched by scripts\fetch_filament.ps1 and built once by scripts\build_filament.ps1 (both git-ignored; about 15 minutes and 6 GB of build tree, placed in %LOCALAPPDATA%\dlss5-vulkan or DLSS5_FILAMENT_BUILD_DIR ; DLSS5_BUILD_JOBS caps the parallel
compiles, default 8, because MSVC takes up to a GB per job on Filament).  Model directory (OpenDLSS-NR.html#model-directory)     nr::Model reads manifest.json : a stages array (each entry: id , file relative to the directory, packedByteLength , sha256 ) and a tensors array (each entry: name , block , layer , parameter , stage , stageOffset , byteLength ). Stage files hold the E4M3 weights as packed bytes; the host re-lays
them out into the matrix forms the kernels consume (src/nr_model.cpp ). Nothing in this repository produces
such a directory. The graph is the 71-block network of 310.8.0 and nothing else: a model with a different block count is refused
at load. Fixtures (OpenDLSS-NR.html#fixtures)     parity compares against recorded captures of the original, which are not part of this repository. A fixture is a
directory with a manifest.json : key    sourceDimensions , fullDimensions  the valid size and the padded field  proxy or inputFeatures  the input: an RGBA f32 image (with conditioning , seed , autoMask ), or the f32 features themselves  checks  what the fixture gates, any of "boundaries" , "head" , "output" ; required and never empty  blocks , transitions  "boundaries" : E4M3 references (block / id , width , height , channels , file )  omittedBoundaries  "boundaries" : {name: reason} for each comparable boundary the fixture has no reference for  referenceHead  "head" : the f32 RGBA head  nativeOutput  "output" : the composed image, dtype "f32" (RGBA halves, needs proxy ) or "u8" (an 8-bit capture)     Everything is validated before the GPU runs, and a fixture that fails any of it is refused: a declared check without
its reference, a reference that is missing, short or names nothing in the graph, a reference no declared check uses,
or a comparable boundary (blocks 0-69, the five encoder transitions) with neither a reference nor a reason. Verdicts
are bit-exact (the pass), equal only up to the sign of zero (a failure), within one code (the 8-bit
capture only, reported apart) or a mismatch; see (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/numerics.md) docs/numerics.md . The head and the output are
compared on the production schedule, resubmitted --repeat times (default 3), which must also agree with the same
graph under barriers; the boundaries come from an instrumented run, whose head must agree with production's. verify additionally needs inputFeatures and a block-0 reference. Tuning switches (OpenDLSS-NR.html#tuning-switches)     All default to the fast, exact route. Every switch keeps the output byte-identical, and parity under each of
them is part of the gate. Any switch that sends a kernel back to GLSL also turns counter chaining off, because
only the PTX kernels take part in it. DLSS5VK_UNFUSED=1 runs the GLSL reference route, up to 2560x1440: it materializes every intermediate. DLSS5VK_PTX_DIR is the PTX directory, default build/ptx . DLSS5VK_CHAIN=0 puts barriers between every launch instead of counter chaining. DLSS5VK_PTX_GEMM , GEMMT , GEMMV , BLOCK32 , FFN , QKV and ATTN set to 0 take one kernel family
back to its GLSL spelling. DLSS5VK_ATTN_STREAM forces streamed global attention off (0) or on (1). DLSS5VK_SPLITK=0 , DLSS5VK_VIT_CHAIN=0 and DLSS5VK_NO_PTX_MLP=1 disable split-K, the ViT chain and the
PTX MLP. DLSS5VK_NO_FUSE_PRE , POOL , UPRES and POST set to 1 drop one fusion each. DLSS5VK_CHAIN_MASK is a bit mask: 1 expert stages, 2 c32 blocks, 4 split GEMMs. Default 3. DLSS5VK_DEFER_MAX is the widest stage whose projection GEMM is fused. Default 128. DLSS5VK_VALIDATION=1 runs under the Khronos validation layer (refused if it is not installed: a Vulkan SDK, or VK_LAYER_PATH at a build of Vulkan-ValidationLayers); an error it reports fails the run. DLSS5VK_DEBUG=1 only prints the driver's own messages (the PTX compiler's among them). DLSS5VK_LIST_EXTENSIONS=1 lists
extensions.  Documentation (OpenDLSS-NR.html#documentation)     (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/README.md) docs/README.md is the index: (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/network.md) network.md is the graph, (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/numerics.md) numerics.md the exactness contract, (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/weights.md) weights.md the layouts, (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/execution.md) execution.md the scheduling, and (https://github.com/maanHimself/OpenDLSS-NR/blob/main/docs/frame.md) frame.md the demo's frame. Not affiliated with NVIDIA (OpenDLSS-NR.html#not-affiliated-with-nvidia)     This project is not affiliated with, endorsed by, or supported by NVIDIA. It contains no NVIDIA software,
weights, headers, or instructions for obtaining them. No rights under any NVIDIA intellectual property are
granted or implied by this repository or its license, and you are responsible for the licenses that apply to
whatever model data you use with it. License (OpenDLSS-NR.html#license)     MIT for everything in this repository ((https://github.com/maanHimself/OpenDLSS-NR/blob/main/LICENSE) LICENSE ). Third-party components are listed in (https://github.com/maanHimself/OpenDLSS-NR/blob/main/NOTICE) NOTICE .          About  A Vulkan reimplementation of NVIDIA's DLSS 5 Neural Rendering network, bit-exact against the original. Resources  (OpenDLSS-NR.html#readme-ov-file)   Readme   (OpenDLSS-NR.html#MIT-1-ov-file)   MIT license   (https://github.com/maanHimself/OpenDLSS-NR/activity)   Activity    Stars    566 stars  Watchers    7 watching  Forks  (https://github.com/maanHimself/OpenDLSS-NR/forks)   58  forks     (https://github.com/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2FmaanHimself%2FOpenDLSS-NR&report=maanHimself+%28user%29) Report repository    Releases     Packages    Contributors    Languages                            Footer (https://github.com)    © 2026 GitHub, Inc.   Footer navigation (https://docs.github.com/site-policy/github-terms/github-terms-of-service) Terms  (https://docs.github.com/site-policy/privacy-policies/github-privacy-statement) Privacy  (https://github.com/security) Security  (https://www.githubstatus.com/) Status  (https://github.community/) Community  (https://docs.github.com/) Docs  (https://support.github.com?tags=dotcom-footer) Contact  Manage cookies    Do not share my personal information              You can’t perform that action at this time.