d4r README

The project's README from github.com/countervolts/d4r. As one markdown file: README.md.

d4r (dlss 4 radeon)

d4r runs NVIDIA's official DLSS Super Resolution library (nvngx_dlss.dll) in Windows games on AMD Radeon GPUs under Linux and Proton. The game asks for DLSS as usual; the DLSS network runs on the AMD GPU through ZLUDA (CUDA on ROCm/HIP), with the heaviest DLSS kernels replaced by hand-written RDNA3 and RDNA4 code.

Supported DLSS models: DLSS 3 CNN (E), DLSS 4 transformer (K, default), and DLSS 4.5 transformer (M). DLSS 5 is not supported.

Proof of concept: d4r shows that DLSS can run on an AMD GPU, but it is not really that practical for everyday use yet. It has been tested on one GPU in a handful of games and depends on unreleased patches to ZLUDA and vkd3d-proton.

See supported games for the tested games and DLSS models.

Not affiliated with NVIDIA or AMD.

Results

DLSS Ultra Performance demo video.

Radeon RX 7700 XT (RDNA3, gfx1101), SILENT HILL Townfall at 2560×1440, every DLSS result is presented in the frame it belongs to (no added latency).

Mode DLSS 3 CNN (preset E) DLSS 4 (preset K) DLSS 4.5 (preset M) FSR 4*
Quality (1705×960) 71.7 fps 67.9 49.3 76.0
Balanced (1488×837) 80.8 75.9 58.0 84.5
Performance (1280×720) 89.7 84.1 69.0 94.0
Ultra Performance (853×480) 89.1 95.5 92.2 107.3

* FSR 4 was measured in an earlier session (2026-09-27); the DLSS columns on 2026-09-29, when the same machine ran about 2–4% slower overall. Run back to back on the same day, this release is faster than 0.1.1 at Quality with every model (E 71.2 → 71.9, K 67.9 → 68.1, M 48.4 → 49.3 fps), and more in games whose DLSS settings differ from Townfall's, whose kernel variants now run natively too.

For reference, native 2560×1440 without upscaling (the game's TSR at 100%) runs at 49.1 fps on the same walk.

On the same GPU DLSS starts at a disadvantage: its networks were designed for NVIDIA's tensor cores, and parts of them still run as translated NVIDIA code. How the numbers were measured, and what each optimisation contributed, is in docs/performance.md.

Known issues

GPU support

d4r builds for RDNA3 and RDNA4. A newly built release compiles native DLSS 4 and 4.5 network kernels for the targets below and selects the matching set at runtime. Only the RX 7700 XT has been tested on a real GPU; RDNA4 runtime and performance remain unverified on hardware.

GPU Chip FP8 math Runtime testing
RX 7700 XT, RX 7800 XT, RX 7700, Radeon PRO W7700 gfx1101 widened to f16 RX 7700 XT only
RX 7900 GRE / XT / XTX, Radeon PRO W7800 / W7900 gfx1100 widened to f16 untested
RX 7600 / 7600 XT, RX 7650 GRE gfx1102 widened to f16 untested
RDNA3 integrated GPUs gfx1103 widened to f16 untested
RX 9070 XT / 9070 / 9070 GRE, Radeon AI PRO R9700 gfx1201 native FP8 (NativeFp8, default on) emulator only
RX 9060 XT / 9060 gfx1200 native FP8 (NativeFp8, default on) compile only
RDNA2 and older unsupported

Native network kernels are built for all listed gfx11/gfx12 targets. Texture kernels are compiled for each target by d4r_emit when supplied to the package script; RDNA4 also has a -fp8 variant. The bridge selects the KFD GPU with the most SIMDs, avoiding an integrated GPU when a discrete GPU is present; D4R_GPU_ARCH overrides that choice. Missing native kernels fall back to ZLUDA. Without the native network kernels, NVIDIA's translated DLSS 4 layers produce invalid values and DLSS discards the network's output, so K loses the transformer's image quality. Preset E does not use the native network kernels.

How it works

game (D3D12) ──► OptiScaler (DLSS inputs) ──► d4r_nvngx.dll  (NGX D3D12 API, tools/d4r_nvngx_shim.cpp)
                                                   │  inputs/output stay in VRAM (vkd3d-proton Vulkan interop,
                                                   │  command list split around DLSS for same-frame results)
                                                   ▼
                          official NGX core + nvngx_dlss.dll  (their CUDA path)
                                                   ▼
                          nvcuda.dll  (Wine CUDA bridge, tools/wine_nvcuda_bridge.c)
                                                   ▼
                          ZLUDA  (patches/zluda: PTX → AMDGPU, WMMA, native kernel overrides)
                                                   ▼
                          native RDNA3 and RDNA4 kernels  (kernels/: DLSS 4 and 4.5 network layers)

Details: docs/architecture.md and docs/native-kernels.md.

Install the release

The release zip works like an OptiScaler release: its contents go into the folder that holds the game's main .exe.

  1. Extract d4r-<version>.zip there. It contains:
    • OptiScaler 0.9.4 as dxgi.dll, with an OptiScaler.ini set up for d4r;
    • the d4r-patched vkd3d-proton (d3d12.dll, d3d12core.dll);
    • an d4r folder with the shim, the CUDA bridge, ZLUDA, the ROCm 7.2.4 runtime, the native kernels, this game's d4r.ini, and NVIDIA's nvngx_dlss.dll (310.7) and _nvngx.dll.
  2. In Steam, select GE-Proton 11 for the game and set these launch options: PROTON_FORCE_NVAPI=1 DXVK_NVAPI_GPU_ARCH=AD100 %command%.

ROCm does not need to be installed: the zip includes its runtime (from AMD's Ubuntu 22.04 packages, which run under Steam's container runtime on any distribution). The zip's NVIDIA files and the kernels built from NVIDIA's code are not covered by this repository's license (see NOTICE). The Proton prefix and the system are not changed. packaging/D4R_README.txt is the full guide that ships in the zip; scripts/package_release.sh builds the zip (see docs/building.md).

Requirements (building from source)

Build and run

The full sequence is in docs/building.md. In short:

  1. Build ZLUDA ee2f25a with patches/zluda/0002–0007 applied, including its d4r_emit example for offline texture builds.
  2. Build the patched vkd3d-proton: scripts/build_vkd3d_proton_d4r.sh OUT_DIR.
  3. Build the shim and bridge: scripts/build_d4r_nvngx_shim.sh, scripts/build_wine_nvcuda_bridge.sh.
  4. Stage the runtime with your NVIDIA files: scripts/install_d4r_runtime.sh _nvngx.dll nvngx_dlss.dll.
  5. Build the native kernels: D4R_ROCM_DIR=… D4R_DLSS_DLL=… D4R_ZLUDA_EMIT=… kernels/build.sh.
  6. Fill in ~/.config/d4r/d4r.ini (created from config/d4r.ini.default on first launch) and start the game with scripts/d4r_play.sh.

The launcher backs up and restores everything it touches in the Proton prefix: OptiScaler.ini, the prefix's d3d12.dll/d3d12core.dll, and the game's Engine.ini when cvars are set.

Preset videos

Gameplay recordings of each DLSS model at the Quality, Performance and Ultra Performance presets.

Ready or Not

Model Quality Performance
DLSS 4.5 video video
DLSS 4 video video
DLSS 3 video video

Townfall

Model Quality Ultra Performance
DLSS 4.5 video video
DLSS 4 video video

Repository layout

Path Contents
tools/ the NGX shim, the Wine CUDA bridge, a D3D12 DLSS harness, probes and kernel replay tools
kernels/ native RDNA3/RDNA4 kernels (k/ DLSS 4, m/ DLSS 4.5, tex/ texture-kernel parts, common/ WMMA layouts), their build script, validation tools and numpy reference models
patches/ ZLUDA and vkd3d-proton patches
scripts/ build, install, launch and probe scripts
config/ the default d4r.ini for the developer launcher
packaging/ the release's d4r.ini, OptiScaler settings, user guide and install check
docs/ architecture, build, native kernel and performance notes

Stars

Star History Chart

License

Apache License 2.0 (see LICENSE). The patches in patches/ are offered under the licenses of the projects they modify: ZLUDA (Apache-2.0 or MIT) and vkd3d-proton (LGPL-2.1). See NOTICE.

To contact me my discord is ._ayo.

d4r (countervolts/d4r)

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288 ·GitHub
What is this?d4r runs NVIDIA's official DLSS Super Resolution library inside Windows games on AMD Radeon GPUs under Linux and Proton, translating the DLSS network through ZLUDA (CUDA on ROCm/HIP) and replacing the heaviest kernels with hand-written RDNA3/RDNA4 code. It supports the DLSS 3 CNN model and the DLSS 4/4.5 transformer models; DLSS 5 is not supported.
How do I install it for a game?Extract the release zip into the folder containing the game's .exe, then in Steam select GE-Proton 11 as the compatibility tool and add the launch options 'PROTONFORCENVAPI=1 DXVKNVAPIGPUARCH=AD100 %command%'. ROCm doesn't need to be installed separately, since its runtime is bundled in the zip.
Do I need NVIDIA's own DLSS files to use this?Yes — you need NVIDIA's nvngxdlss.dll (310.7) and a matching nvngx.dll, since those files and the kernels built from NVIDIA's code aren't covered by d4r's own license. Building from source instead also needs ROCm with HIP, a GE-Proton build with OptiScaler integration, Rust, git-lfs, meson/ninja and MinGW/clang-cl toolchains.
Is this ready for everyday gaming?No — the author describes it as a proof of concept, tested on only one GPU (an RX 7700 XT) in a handful of games, and it depends on unreleased patches to ZLUDA and vkd3d-proton. RDNA4 behavior is unverified on real hardware, and some games show visible artifacting with native upscaling.
Will this work on my Radeon GPU?Only RDNA3 cards (RX 7700/7800/7900 series, gfx1100-1103) and RDNA4 cards (RX 9060/9070 series, gfx1200/1201) are targeted by the native kernels; RDNA2 and older GPUs are unsupported, and only the RX 7700 XT has actually been tested on real hardware so far.
How much does d4r actually speed things up?On an RX 7700 XT in SILENT HILL Townfall, DLSS Quality runs at roughly 67-72 fps versus 49.1 fps for native rendering, though it still trails AMD's own FSR 4 at the same settings.
Is this an official NVIDIA or AMD project?No, the README explicitly states d4r is not affiliated with NVIDIA or AMD.
How does the DLSS translation pipeline actually work?A D3D12 shim intercepts the game's NGX calls that OptiScaler forwards, a Wine-side CUDA bridge relays them to ZLUDA, ZLUDA translates NVIDIA's PTX code for the AMD GPU, and hand-written native kernels replace the heaviest DLSS network layers for speed.
What happens if native kernels aren't available for my GPU?The bridge falls back to ZLUDA's generic PTX translation, but without the native kernels, NVIDIA's translated DLSS 4 transformer layers produce invalid output that gets discarded, degrading image quality.
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