The eleven cuda_dldn_engine_swin_* layers have to be written natively before
the denoiser can come close to 5 ms, and that needs their layout: which maximal
runs of mma exist, what tile each covers, and which bytes of the 54 KB weight
image it reads.
rr_layer_spec.py derives that from the extracted PTX and nothing else - no GPU,
no dependencies beyond the standard library. A phase is one maximal run of
adjacent mma statements; M, N and K come from the number of distinct A and B
fragments and the length of the accumulator chains partitioned by their D-to-C
dataflow, rather than from a guess at the geometry; and each phase reports the
weight and bias byte offsets it reads and the size of the epilogue that follows.
Statement ranges carry their physical PTX line, so every claim can be checked
with sed.
enc0 comes out as 22 phases: two stem projections (M96 N32 K32), the fused Q/V
projection (M96 N32 K32 x2), the score phase (M64 N96 K32, bias 8384..20172 -
a 24-tile 16x16-per-head table), the banded P*V phase (M192 N96 K96, no weight
operand at all), the output projection, then the second window's copy of the
same pair, then the MLP phases and the M64 N256 K128 merge. The weight extents
it reports agree with the harness dump to within a 12-byte unpadded tail
(54548 against 54560 for enc0), and the widest phase gives each layer's
patch-merge or patch-expand width.
D4R_CUDA_LAUNCH_STATS=1 synchronizes after and dumps every argument of every
launch, which costs about 1.2 GB and 5 s per frame - fine for a one-off
inventory, too much for the edit/measure loop of a single kernel.
D4R_CUDA_LAUNCH_STATS_FILTER=<substring> keeps only the kernels whose name
contains it, and is checked before the synchronize so the rest of the frame is
neither waited on nor written.
Verified: with the filter set to swin_enc0 the dump is 54 files / 839 MB
instead of 314 / 3.7 GB, the run takes 5 s instead of 17, and the 54 argument
files are byte-identical to the ones the unfiltered run produced.
The bridge's other instrumentation - D4R_CUDA_LAUNCH_STATS with
D4R_CUDA_LAUNCH_DUMP_DIR - already dumps every allocation, surface object and
texture object named in a launch's packed argument buffer, after the launch has
finished. That is enough to check one reimplemented kernel on its own: the
translated kernel's surface files are its output, and a native replacement has
to reproduce them.
What was missing was the comparison. compare_launch_dump.py keys the files by
kernel, argument offset, kind, shape and format rather than by the global launch
sequence, so a replacement that adds launches of its own does not break the
alignment, and it reports the first differing byte per argument.
Verified end to end today: cuda_dldn_engine_swin_enc0_kernel's PTX module was
compiled offline with d4r_emit, served from a native directory (the bridge logs
`[d4r-native] "cuda_dldn_engine_swin_enc0_kernel" -> ...hsaco`), and its run is
byte-identical to the translated one across all 54 of its dumped arguments -
weight image, activation buffer, four output surfaces. That also shows the
offline build reproduces the loader's own compile exactly, which every native
denoiser layer will rest on.
docs/native-kernels.md gains the dump-and-diff step, which is the only way to
localise a mismatch to one of the eleven layers that sample textures and write
surfaces.
Ray Reconstruction's eleven DLSS-D Swin layers still run ZLUDA's compile of
NVIDIA's PTX; at 1280x720 -> 3840x2160 on gfx1201 they are 30.2 of a 31.6 ms
frame. The denoiser's high-fidelity output kernel is the first one with a native
replacement: make_ptx.py replaces its whole-texel RGBA16F store
(sust.b.2d.v4.b16.zero) through d4r_sust_v4b16, kernels/build.sh builds the pair
as the `rr` family, and packaging builds it into every target folder including
the RDNA4 FP8 ones.
Both libraries define modules named cuda_dldn_engine_*, with different text, so
one manifest cannot take the union of their hashes: kernel_manifest.py now takes
the denoiser DLL as --rr-dll and lets only its hashes authorize a
cuda_dldn_engine_* binary, and package_release.sh passes it when the denoiser is
bundled.
Verified in the D3D12 harness with Ray Reconstruction at 1280x720 -> 3840x2160:
the output kernel drops from 1.44 to 1.00 ms/frame and the 66 MB raw output is
byte-identical to the run with every kernel translated.
docs/native-kernels.md gains the denoiser family, the per-kernel cost table and
the instruction counts that show why the Swin layers are the remaining work.
Run the signed CUDA-capable denoiser through feature 13 with independent D/E presets, pre-Init discovery, per-frame guide and camera snapshots, normalized integer guide staging, paired alpha output, and recorded-resource retirement.
Add the required ZLUDA/LLVM patch, behavioral configuration tests, GPU harness coverage, optional denoiser installation and packaging, and tested support limitations. Preserve upstream attribution and distinguish LLVM licensing from the ZLUDA portions of the patch.
A standalone Vulkan inference engine (engine/) for DLSS presets K and M that
runs from weights extracted from the user's own nvngx_dlss.dll, with d4r's
own input, network and reconstruction shaders or the native HIP network
layers, recorded into the game's command list by the shim. Opt-in
([Engine] Enabled / D4R_ENGINE=1); anything uncovered falls back to the
CUDA/ZLUDA path with the reason logged.
Byte-identical to NGX's CUDA backend under the phase-capable reference
(1706x960 -> 2560x1440, native HIP network, eleven frames, RX 9070 XT):
- K render- and display-resolution motion vectors, HDR and LDR
- K game-supplied exposure and automatic exposure with any pre-exposure
and exposure scale (one residual: effective exposure exactly 2 or 4)
- K and M with the DLSS indicator's inverted-axis parameters
- M with any exposure settings (NGX ignores them for M)
K packages need the current compile_k.py (marker D4RO0003).
Also: HIP shared buffers are pooled across feature recreation (ROCm leaks
destroyed imports), hipnet.bin must match the preset, M-only games do not
load the K model, install_d4r_runtime.sh stages k, k-ldr, m, m-ldr with
hip/, the activation table has a generator (gen_activation_m.py), and
package_release.sh can bundle the engine's shaders (never its weights).
Signed-off-by: woutermans <[email protected]>
Implement NGX's Vulkan API over the existing CUDA backend. Compute shaders
pack the game's sampled images into buffers shared with CUDA (device-local
memory exported through the Wine bridge), and a device event in the game's
command buffer holds its queue until the result is written back, keeping
frame age at zero. DLSS reads inputs through pitch-linear textures and its
native output kernel writes the shared buffer directly; input and
completion waits are adaptive.
Make it work across engines: shared buffers are concurrent over every
compute-capable queue family (Indiana Jones records DLSS on async compute),
depth kept in an R32F colour image is accepted under a depth aspect, and the
extension-requirement query allows a null list. Spare buffer sets are
imported on the first frame and never while a frame is pending, since an
import can block on GPU work that is waiting for us; host staging covers any
shortfall.
Fix two exit hazards. A game quitting without NGX shutdown left the GPU
waiting on an event that only a killed thread would set, resetting the ring
10 s later: the bridge now runs a shim hook before teardown and skips all
CUDA destroy/sync calls once Wine is shutting the process down. The shim's
own entry point skips CRT static destructors at process termination, where
locks held by killed threads made the exit spin forever.
Add a Vulkan DLSS harness (dynamic, recreate, discard, invalid, exit,
compute-queue and in-flight modes), staging/depth probes, ABI/config tests,
and an OptiScaler settings overlay for Vulkan games.
NVIDIA's enc1 and enc2 clamp the patch merge's result to ±2π (as f16) before
its e4m3 encoding (max.f16x2 / min.f16x2 with 0fC0C90FDB / 0f40C90FDB after the
merge's last MMA). The native layers did not, in either template or set:
merge_clamp (swin_common.h) now does, at the three sites that encode the merged
tokens (swin_block.h's e4m3-activation and f16 paths, swin_tok.h), and
swin_check.py's model clamps the same way.
Measured on an RX 9070 XT against a run with no native kernels (preset L,
accuracy set, the flags of Ghost of Tsushima, 1280x720 -> 3840x2160, one
frame): native enc1 alone 34 dB and enc2 alone 31 dB from the translated
kernels before, byte-identical after; the whole native set 28 -> 80 dB (the
rest is dec1, 0.09% of the output values). Preset M's fast set against
translated M: 30.8 -> 35.1 dB after 30 frames. The gfx11 path has the same
change and was not run on hardware.
The repo's tests pass (36, 3 skipped).
L's unfolded enc0 and dec0 are still ZLUDA's compile of NVIDIA's PTX and cost
2.95 ms of the preset's 5.86 ms per frame (RX 9070 XT, 1280x720 -> 4K). The
embedding, the patch expand, the Swin block (32 channels, 2 heads, at pixel
resolution) and the patch merge are now native token-lane code; the texture
work around them stays ZLUDA's compile.
enc0l_tail.hip cuts in at the barrier after the feature staging and dec0l_block.hip
before the output code that reads the block's f16 result out of the last MMAs; make_ptx.py
splices either in when D4R_TEX_SRC names it and build.sh selects both for the gfx12
native-FP8 builds. swin_tex.h carries the indexing the two tails share; swin_tok.h gains
the pixel-order token layout (SWIN_TOK_NATURAL), ZLUDA's attention key order
(SWIN_PV_ZLUDA_ORDER) and swin_tok_core, which the encoded tests reuse. swin_common.h
takes the block weight layout (moved out of swin_block.h) and the exact and approximate
reciprocal / mix forms the tails need without the HIP headers (D4R_NO_HIP_RUNTIME).
The f32 sums stay in ZLUDA's order (K slots of the FP8 WMMAs, key order of the f16
attention product) and rsqrt/rcp use the hardware approximations ZLUDA lowers to, so the
harness's final frame is byte-identical to the translated kernels: all four enc0 flag
variants, 720p and 1080p render, 1440p and 4K output, static and moving scenes, 100
frames, and the accuracy set. With M's own sum order about one token in 20,000 differed.
M's layers compile to the same instructions and its frame is byte-identical.
enc0 1.69 -> 0.63 ms and dec0 1.26 -> 0.54 ms at 720p->4K, 2.73 -> 1.16 and 2.28 -> 1.01
at 1080p->4K; the preset 5.83 -> 4.06 and 8.63 -> 5.69 ms. -DD4R_SWIN_K32_MIX rounds the
f16 products earlier for 0.56 and 0.49 ms and is not byte-identical, so it is not built by
default. The repo's tests pass (36, 3 skipped).
- Add docs/in-place-inputs.md: reading the DLSS inputs in place does not work,
because a hardware texture fetch on a HIP texture object over memory imported
from vkd3d-proton returns stale data while plain loads and cuMemcpy2D are
correct; records the measurements, the rule-outs and the reworked-fetch
workaround that turned out not to pay for itself.
- Add tools/hip_vk_texture_stale_repro.cpp and its build script, the native
Vulkan + HIP reproducer that rules out a general ROCm or RADV bug.
- Tag redirected surfaces as R10G10B10A2 ('R3') as well as RGBA16F ('R2'), and
let the native output kernel store the game's R10G10B10A2 texels itself.
- Import linear, exportable game textures (vkd3d-proton patch 0003) into HIP
so the output kernel writes the game's output texture with no game-side copy.
- Add ID3D12DXVKInteropDeviceD4R3 with GetVulkanLinearImageInfo.
- Gate both paths behind D4R_SHIM_OUTPUT_PACKED and D4R_SHIM_INPLACE, and use
them only for split frames of preset M whose output kernel honours the redirect.
- Convert on the host when a recorded packed frame finds the wrong kernel.
- Give the harness an R10G10B10A2 output, and add D4R_SHIM_SPIN_POLL so
frame timing is not quantised to the poll sleep.
- Document the measured removal of the output copies in performance.md.
make_ptx.py turns the 32 cvt.rn.f16x2.e4m3x2 of rrlite_dec0_4x4_folded into calls of d4r_dec_e4m3x2 (tex_common.h) when D4R_TEX_FP8=1: v_cvt_pk_f32_fp8 and two conversions to f16 instead of ZLUDA's integer lowering (about 25 instructions each; the kernel goes from 4058 to 3418 instructions). The conversion equals ZLUDA's e4m3_to_f16_bits for every code except the NaN codes 0x7f / 0xff, checked over all 65536 code pairs on an RX 9070 XT, and the head never stages those codes (it clamps to +-448 before encoding). Harness frames are byte-identical in the accuracy and the fast set, over a 16-frame moving sequence in the accuracy set. dec0 at 2227x1253 render: 0.43 -> 0.38 ms (accuracy), 0.36 -> 0.30 ms (fast). -DD4R_TEX_SOFT_E4M3 gives ZLUDA's lowering; builds without D4R_TEX_FP8 keep the PTX instruction.
On the gfx12 native-FP8 path the enc0 tail and the dec0 head encode their results with v_cvt_pk_fp8_f32 on the f32 copies of the f16 values (e4m3x4_f32 in tex_common.h) instead of ZLUDA's integer e4m3x2. The clamps keep the conversion in range: +-2pi for enc0 (the f16 bound hi[0], same in f32) and +-448 for dec0, both as a median of three, where a NaN gives the lower bound. The codes equal e4m3x2 for every non-NaN f16, checked over all 65536 patterns on an RX 9070 XT; a NaN in dec0 now encodes as -448 instead of the NaN code. Harness frames are byte-identical in both sets (LDR and HDR, motion vectors at render and display resolution). dec0: 0.21 -> 0.15 ms at 1280x720 render and 0.74 -> 0.53 ms at 2560x1440; enc0 changes by 1-2% (its time is ZLUDA's compile of the feature code). -DD4R_TEX_SOFT_E4M3 (D4R_TEX_CFLAGS) keeps e4m3x2.
The remaining two layers (96 channels, four heads) use the same swin_tok.h template: byte-identical on the same recorded launches and harness sequences, enc2 0.22 -> 0.14 ms and dec2 0.20 -> 0.14 ms at 1280x720 render, 0.75 -> 0.47 and 0.69 -> 0.47 ms at 2560x1440. Skipping windows that lie entirely outside the image is also exact but below the measurement noise (at most 2.4% of the windows of every other tube launch), so it is not kept; true16 code generation remains not tried.
swin_tok.h passes the weights as the first WMMA operand and the activations as the second, so each GEMM's encoded result is already the next one's operand and stays in registers (swin_block.h transposes every result through LDS). One wave owns one 4x4 window for the whole block: norms, attention and the MLP need no LDS and no barriers; only the patch expand and the patch merge go through an e4m3 image in LDS. Outputs are bit-identical to swin_block.h (swapped WMMA operand roles, verified on an RX 9070 XT and on recorded launches). mix2 rounds in place (accumulator is addend and destination, no copy per pair). -DSWIN_NO_TOKEN_LANES builds these layers from swin_block.h again; enc2 and dec2 are unchanged. RX 9070 XT accuracy set, 2560x1440 render: whole evaluation 8.56 -> 7.18 ms.
The 2x figure is against the previous native-FP8 layers. With NativeFp8 off
the RX 9070 XT was already at 3.37 ms for 1280x720 -> 3840x2160; the FP8 set
is 2.88 ms there.
The FP8 Swin layers encode with a clamp to +-448 (NaN-propagating packed
minimum/maximum) followed by v_cvt_pk_fp8_f32, in both the fast and the
accuracy build: equal to half_to_e4m3 for every non-NaN input, NaN encodes
as 0xff. The accuracy build rounds each k32 step with v_fma_mix (K32_MIX).
On gfx12 the accuracy builds of M's post and downsample kernels are wave64
with denormal handling kept.
RX 9070 XT, 1280x720 -> 3840x2160, D3D12 harness: the accuracy set goes
from 3.54 ms to 3.05 ms per evaluation (3.01 -> 2.59 ms under load). Its
Swin layers still equal swin_model.py on sampled blocks and its image is
byte-identical to the previous accuracy set over 8 temporal frames.
On the gfx12 native-FP8 path the Swin layers kept GEMM activations as f16
in LDS and encoded them to e4m3 again at every operand load. They are now
encoded once where they are produced, with v_cvt_pk_fp8_f32, and stored as
bytes (SWIN_A8); the patch merge reads the stored output codes. The M
downsample kernels are built as wave64 on gfx12.
RX 9070 XT, 1280x720 -> 3840x2160, D3D12 harness, DLSS 310.7: whole
evaluation 5.9 ms -> 2.8 ms of GPU time with the GPU otherwise idle, 2.4 ms
at 80-98% GPU utilisation. Harness output is byte-identical to the previous
kernels; the accuracy build matches swin_model.py on sampled blocks.
Builds without D4R_FP8_WMMA (RDNA3, and RDNA4 with NativeFp8 off) compile to
the same instructions as before.
Preset K, byte-identical to the previous output in all captured buffers
and the harness image, measured on an RX 7700 XT:
- LDS row padding so WMMA operand loads hit distinct banks
- WGP mode for enc1/enc2/dec1/dec2, ds_bpermute half-wave exchange for
enc0/dec0/dec3, more waves per window in enc4/dec4/dec5
- cheaper operand plumbing in common/wmma_layout.h (packed f16
conversions, no dynamic vector indexing), raw buffer weight loads,
accumulator-init vectors prepared once
- enc1 as a single-buffer recompute layer, dec1 Q/K/V chains split
- dec5 as four dependent phase kernels
- Reprepare enc3 weights each launch to avoid stale caches after feature recreation
- Require per-slot input markers before evaluating recorded frames
- Advance split-frame timelines only through completed frames
- Add cancellation and readiness tests plus recreation consistency checks
- Update architecture and native kernel documentation
ref #8
- Explicitly route OptiScaler to d4r\nvngx.dll in release packages.
- Extract INI generation into a helper that preserves line endings
and rejects missing or duplicate settings.
- Check NGX routing separately from file presence and return failure
when the installation is incomplete or misconfigured.
- Add an optional OptiScaler patch for external DLSS backends while
preserving AMD identity for FSR4, with matching launch guidance.
- Align portable and launcher marker polling defaults at 200 us.
- Log when d4r's model override replaces game or OptiScaler presets.
- Add configuration, package, routing and coexistence regression tests.
- Update installation documentation, add FSR/DLSS comparison videos
and ignore local .tools artifacts.
Refs: #7, #14
- Add default-off PreferAccuracy for all native kernel families,
including RDNA4 FP8 variants.
- Restore intermediate FP8 quantization, per-MMA FP16 rounding,
denormal handling and NGX synchronization in accuracy mode.
- Select separately marked accuracy kernels and use a separate JIT
cache; reject mixed sets and never silently substitute fast kernels.
- Add a pinned GLIBC 2.41 build environment for ZLUDA/LLVM, the DLLs
and both kernel sets, with ABI checks and toolchain provenance.
- Support parallel target builds and pre-extracted PTX; correct
ROCm header paths and Clang-CL input handling.
- Bump to 0.1.3 and update release notes, documentation and tests.
Validation: 11 tests passed; all 912 kernels built; E/K/M GPU harness
runs completed with accuracy off/on. Packaged libraries loaded under
GLIBC 2.41 and require no GLIBC version newer than 2.38.
RTX image-quality parity remains unverified.
Fixes#6
Refs #6
- Fix Cyberpunk 2077 preset-K black artifacts by preserving FP16/FP64
denormal requirements while limiting denormal suppression to FP32.
- Fix stale direct-output redirects after array destruction, preventing
reused handles from inheriting an earlier feature's output buffer.
- Log rejected resource formats and dimensions, including failures after
startup, with rate limiting for repeated errors.
- Add opt-in blocking output synchronization with a dedicated bridge
export and fallback to context synchronization.
- Report output-wait CPU and wall time, and defer GPU timing queries
until asynchronous evaluation has completed. The CPU-overhead
mitigation for #7 still needs reporter confirmation.
- Reject release libraries requiring GLIBC newer than the configured
baseline, defaulting to 2.41, and document compatible builds.
Validation: shim and bridge builds pass; targeted redirect-lifetime and
format-logging checks pass.
Fixes#5Fixes#8
Refs #7
RDNA4 (experimental; untested on RDNA4 hardware)
- kernels/common/wmma_layout.h picks the WMMA operand/accumulator layout
per target; K (pwin_*) and M (swin_*) index through it, so the same
sources build for gfx11 and gfx12. D4R_WMMA_LAYOUT=12 on gfx11 is a test
shim that runs the gfx12 indexing on gfx11 WMMA.
- M can use native e4m3 FP8 WMMA on gfx12 (D4R_NATIVE_FP8=1). Texture
tails (enc0_tail, dec0_head) get gfx12 f16 and FP8 paths that match
ZLUDA's gfx12 lowering.
- ZLUDA patch 0007: gfx12 WMMA helpers, optional native FP8 MMA
(D4R_ZLUDA_WMMA_FP8_NATIVE), a layout override for testing, and an
architecture argument for d4r_emit. Texture kernels are now compiled
offline per target through d4r_emit (D4R_ZLUDA_EMIT) instead of on the
local GPU.
- New d4r.ini option [Kernels] NativeFp8 (default on), wired through the
shim and d4r_config.py. On gfx12 the bridge serves kernels/<arch>-fp8
when it is on.
- The bridge picks the KFD GPU with the most SIMDs (so an iGPU is not
chosen over a discrete GPU); D4R_GPU_ARCH overrides it.
- kernels/build.sh and package_release.sh build gfx1100-gfx1103 and
gfx1200/gfx1201 (plus -fp8 variants), and D4R_BUNDLE_TEX takes
per-target folders.
Performance (RDNA3; harness byte-identical unless noted)
- ZLUDA patch 0006: m16n8k8 f16 MMAs on WMMA (E; not bit-exact, 52-55 dB
per layer, D4R_ZLUDA_WMMA_K8=0 disables it), per-key weight-image slots
for native prep kernels (d4r_prep_key_at, d4r_prep_key_slots), and
wave64 builds of MMA-free kernels (D4R_ZLUDA_WAVE64).
- M: packed FP8 encoding, conflict-free patch-merge reads, scalar weight
loads in enc1, and weight prep once per weight set for the six enc3
tube blocks.
- K: CU mode for the six non-wide pwin layers.
- Texture kernels: every DLSS flag variant is built natively (24 K output,
8 M post, 4 M downsample, 4 M enc0), not only Townfall's; post and K
output run as wave64.
- M direct output: rrlite_downsample_kernel writes the shim's output
buffer; the shim's default direct-output presets are now 11,13.
Tools
- dump_runner takes the prep grid from d4r_prep_blocks and refuses
texture/surface dumps.
- New pwin_check.py, swin_check.py, model_enc3.py and tail_check.hip.
Docs: README GPU table and RDNA4 notes, building (patches 0002-0007,
d4r_emit), native-kernels (RDNA4 section), performance (new numbers),
packaging README. Version 0.1.2.
woutermans