Add native K/M/RR inference engines, HIP kernels, replay and validation harnesses, and Windows DLSS setup and runtime support. Include GPU profiling tools, build and packaging scripts, platform integration patches, and implementation documentation.
158 lines
7.5 KiB
C++
158 lines
7.5 KiB
C++
#pragma once
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#include "cuda_api.h"
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namespace d4r::cuda {
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// Public CUDA Driver API layouts, kept independent of NVIDIA SDK headers.
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using Array = void*;
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using Texture = uint64_t;
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struct ArrayDescriptor { size_t width, height; uint32_t format, channels; };
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struct Array3DDescriptor {
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size_t width, height, depth;
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uint32_t format, channels, flags;
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};
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struct Copy2D {
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size_t srcX, srcY;
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uint32_t srcType, srcAlignment;
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const void* srcHost;
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CUdeviceptr srcDevice;
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Array srcArray;
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size_t srcPitch, dstX, dstY;
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uint32_t dstType, dstAlignment;
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void* dstHost;
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CUdeviceptr dstDevice;
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Array dstArray;
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size_t dstPitch, widthBytes, height;
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};
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struct ResourceDescriptor {
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uint32_t type, alignment;
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union { Array array; int reserved[32]; } resource;
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uint32_t flags, reserved;
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};
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struct TextureDescriptor {
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uint32_t addressMode[3], filterMode, flags, maxAnisotropy, mipmapFilterMode;
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float mipmapBias, minMipmapClamp, maxMipmapClamp, borderColor[4];
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int reserved[12];
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};
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static_assert(sizeof(Array3DDescriptor) == 40);
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static_assert(sizeof(ArrayDescriptor) == 24);
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static_assert(sizeof(Copy2D) == 128);
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static_assert(sizeof(ResourceDescriptor) == 144);
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static_assert(sizeof(TextureDescriptor) == 104);
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struct ImageApi {
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CudaApi& cuda;
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#define D4R_IMAGE(name, ...) using name##_fn = int(WINAPI*)(__VA_ARGS__); name##_fn name = cuda.library.symbol<name##_fn>(#name)
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D4R_IMAGE(cuArray3DCreate_v2, Array*, const Array3DDescriptor*);
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D4R_IMAGE(cuArrayGetDescriptor_v2, ArrayDescriptor*, Array);
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D4R_IMAGE(cuArray3DGetDescriptor_v2, Array3DDescriptor*, Array);
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D4R_IMAGE(cuArrayDestroy, Array);
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D4R_IMAGE(cuMemcpy2D_v2, const Copy2D*);
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D4R_IMAGE(cuMemcpy2DAsync_v2, const Copy2D*, void*);
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D4R_IMAGE(cuTexObjectCreate, Texture*, const ResourceDescriptor*, const TextureDescriptor*, const void*);
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D4R_IMAGE(cuTexObjectDestroy, Texture);
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D4R_IMAGE(cuTexObjectGetResourceDesc, ResourceDescriptor*, Texture);
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D4R_IMAGE(cuSurfObjectCreate, Texture*, const ResourceDescriptor*);
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D4R_IMAGE(cuSurfObjectDestroy, Texture);
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D4R_IMAGE(cuSurfObjectGetResourceDesc, ResourceDescriptor*, Texture);
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#undef D4R_IMAGE
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explicit ImageApi(CudaApi& api) : cuda(api) {}
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};
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class Image {
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ImageApi& api_;
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void release() noexcept {
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if (object) {
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const int result = surface_ ? api_.cuSurfObjectDestroy(object) : api_.cuTexObjectDestroy(object);
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if (result) std::fprintf(stderr, "IMAGE_DESTROY object result=%d\n", result);
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object = 0;
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}
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if (array_) {
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const int result = api_.cuArrayDestroy(array_);
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if (result) std::fprintf(stderr, "IMAGE_DESTROY array result=%d\n", result);
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array_ = nullptr;
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}
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}
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Array array_ = nullptr;
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bool surface_;
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size_t rowBytes_, height_;
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public:
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Texture object = 0;
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Image(ImageApi& api, unsigned width, unsigned height, uint32_t format,
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unsigned channels, bool surface, unsigned filter = 0)
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: api_(api), surface_(surface), rowBytes_(size_t(width) * channels * (format == 16 ? 2 : 4)), height_(height) {
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try {
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const Array3DDescriptor descriptor{width, height, 0, format, channels, surface ? 2u : 0u};
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api_.cuda.check(api_.cuArray3DCreate_v2(&array_, &descriptor), "cuArray3DCreate_v2");
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ResourceDescriptor resource{};
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resource.resource.array = array_;
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if (surface) api_.cuda.check(api_.cuSurfObjectCreate(&object, &resource), "cuSurfObjectCreate");
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else {
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TextureDescriptor texture{};
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texture.addressMode[0] = texture.addressMode[1] = 1; // clamp
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texture.filterMode = filter;
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texture.flags = 2; // normalized coordinates
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api_.cuda.check(api_.cuTexObjectCreate(&object, &resource, &texture, nullptr), "cuTexObjectCreate");
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}
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ResourceDescriptor roundtrip{};
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api_.cuda.check(surface ? api_.cuSurfObjectGetResourceDesc(&roundtrip, object) :
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api_.cuTexObjectGetResourceDesc(&roundtrip, object), "CUDA object resource descriptor roundtrip");
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if (roundtrip.type != 0 || roundtrip.resource.array != array_ || roundtrip.flags != 0)
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throw std::runtime_error("CUDA object descriptor does not match its array");
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ArrayDescriptor twoD{};
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Array3DDescriptor threeD{};
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api_.cuda.check(api_.cuArrayGetDescriptor_v2(&twoD, array_), "cuArrayGetDescriptor_v2");
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api_.cuda.check(api_.cuArray3DGetDescriptor_v2(&threeD, array_), "cuArray3DGetDescriptor_v2");
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if (twoD.width != width || twoD.height != height || twoD.format != format || twoD.channels != channels ||
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threeD.width != width || threeD.height != height || threeD.depth != 0 || threeD.format != format ||
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threeD.channels != channels || threeD.flags != descriptor.flags)
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throw std::runtime_error("CUDA array descriptor geometry or format mismatch");
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} catch (...) { release(); throw; }
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}
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Image(const Image&) = delete;
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Image& operator=(const Image&) = delete;
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~Image() { release(); }
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void verify_wrong_object_kind() {
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ResourceDescriptor wrong{};
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const int result = surface_ ? api_.cuTexObjectGetResourceDesc(&wrong, object) :
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api_.cuSurfObjectGetResourceDesc(&wrong, object);
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if (!result) throw std::runtime_error("Wrong CUDA object kind was accepted as a valid resource");
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std::printf("CUDA wrong-kind descriptor safely rejected result=%d\n", result);
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}
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void upload(const void* source) {
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Copy2D copy{};
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copy.srcType = 1; copy.srcHost = source; copy.srcPitch = rowBytes_;
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copy.dstType = 3; copy.dstArray = array_;
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copy.widthBytes = rowBytes_; copy.height = height_;
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api_.cuda.check(api_.cuMemcpy2D_v2(©), "cuMemcpy2D_v2(host to diagnostic array)");
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}
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void download(void* destination) {
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Copy2D copy{};
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copy.srcType = 3; copy.srcArray = array_;
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copy.dstType = 1; copy.dstHost = destination; copy.dstPitch = rowBytes_;
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copy.widthBytes = rowBytes_; copy.height = height_;
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api_.cuda.check(api_.cuMemcpy2D_v2(©), "cuMemcpy2D_v2(diagnostic array to host)");
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}
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void upload_device(CUdeviceptr source, size_t pitch, bool deferred = false) {
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if (pitch < rowBytes_) throw std::runtime_error("Device input pitch is smaller than its row");
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Copy2D copy{};
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copy.srcType = 2; copy.srcDevice = source; copy.srcPitch = pitch;
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copy.dstType = 3; copy.dstArray = array_;
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copy.widthBytes = rowBytes_; copy.height = height_;
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if (deferred) {
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// The Windows ZLUDA backend and HIP conversion use the same
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// legacy default stream. Caller must complete the whole input
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// batch before NGX may consume arrays on its own streams.
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api_.cuda.check(api_.cuMemcpy2DAsync_v2(©, nullptr), "cuMemcpy2DAsync_v2(external VRAM to array)");
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} else api_.cuda.check(api_.cuMemcpy2D_v2(©), "cuMemcpy2D_v2(external VRAM to array)");
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}
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void download_device(CUdeviceptr destination, size_t pitch) {
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if (pitch < rowBytes_) throw std::runtime_error("Device output pitch is smaller than its row");
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Copy2D copy{};
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copy.srcType = 3; copy.srcArray = array_;
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copy.dstType = 2; copy.dstDevice = destination; copy.dstPitch = pitch;
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copy.widthBytes = rowBytes_; copy.height = height_;
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api_.cuda.check(api_.cuMemcpy2D_v2(©), "cuMemcpy2D_v2(array to external VRAM)");
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}
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};
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}
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