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Add transpose kernels #22
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austinvhuang
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AnswerDotAI:main
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junjihashimoto:feature/transpose
Jul 29, 2024
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,27 @@ | ||
CXX=clang++ | ||
GPUCPP ?= $(PWD)/../.. | ||
LIBDIR ?= $(GPUCPP)/third_party/lib | ||
LIBSPEC ?= . $(GPUCPP)/source | ||
NUM_JOBS?=$(shell nproc) | ||
CODEPATH = find . ../../utils ../../ -maxdepth 1 -type f | ||
TARGET=transpose | ||
ifeq ($(shell $(CXX) -std=c++17 -x c++ -E -include array - < /dev/null > /dev/null 2>&1 ; echo $$?),0) | ||
STDLIB := | ||
else | ||
STDLIB := -stdlib=libc++ | ||
endif | ||
FLAGS=-std=c++17 $(STDLIB) -I$(GPUCPP) -I$(GPUCPP)/third_party/headers -L$(GPUCPP)/third_party/lib run.cpp -ldl -ldawn | ||
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run: ./build/$(TARGET) | ||
$(LIBSPEC) && ./build/$(TARGET) | ||
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# Use clang -v to see the include paths | ||
build/$(TARGET): run.cpp | ||
mkdir -p build && $(CXX) $(FLAGS) -o ./build/$(TARGET) | ||
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watch: | ||
@command -v entr >/dev/null 2>&1 || { echo >&2 "Please install entr with 'brew install entr' or 'sudo apt-get install entr'"; exit 1; } | ||
mkdir -p build && $(CODEPATH) | entr -s "$(LIBSPEC) && rm -f ./build/$(TARGET) && make -j$(NUM_JOBS) ./build/$(TARGET) && ./build/$(TARGET)" | ||
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clean: | ||
read -r -p "This will delete the contents of build/*. Are you sure? [CTRL-C to abort] " response && rm -rf build/* |
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,241 @@ | ||
#include <array> | ||
#include <chrono> | ||
#include <future> | ||
#include <random> | ||
#include <cstdlib> | ||
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#include "gpu.h" // createContext, createTensor, createKernel, dispatchKernel, | ||
// wait, resetCommandBuffer, toCPU | ||
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#include "llmc/reference_impls.h" // for CPU reference implementation | ||
#include "utils/array_utils.h" // show, isclose, randn, randint | ||
#include "utils/logging.h" // LOG | ||
#include "experimental/wgsl.h" // loopUnrolling | ||
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using namespace gpu; | ||
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// This implements the tranpose kernels in https://developer.nvidia.com/blog/efficient-matrix-transpose-cuda-cc . | ||
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static const char *kShaderTranspose1 = R"( | ||
@group(0) @binding(0) var<storage, read_write> A: array<{{precision}}>; | ||
@group(0) @binding(1) var<storage, read_write> B: array<{{precision}}>; | ||
@compute @workgroup_size({{workgroupSize}}) | ||
fn main( | ||
@builtin(global_invocation_id) globalID : vec3<u32>) { | ||
let bRow: u32 = globalID.x; | ||
let bCol: u32 = globalID.y; | ||
B[bRow * {{M}} + bCol] = A[bCol * {{N}} + bRow]; | ||
} | ||
)"; | ||
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inline KernelCode createTranspose1(const char *shaderTemplate, | ||
const size_t M, const size_t N, | ||
const Shape &workgroupSize = {256, 1, 1}, | ||
NumType precision = kf32) { | ||
std::string codeString(shaderTemplate); | ||
replaceAll(codeString, {{"{{workgroupSize}}", toString(workgroupSize)}, | ||
{"{{precision}}", toString(precision)}, | ||
{"{{M}}", toString(M)}, | ||
{"{{N}}", toString(N)}}); | ||
return {codeString, workgroupSize}; | ||
} | ||
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// Shared memory cache-blocking | ||
static const char *kShaderTranspose2 = R"( | ||
@group(0) @binding(0) var<storage, read_write> A: array<{{precision}}>; | ||
@group(0) @binding(1) var<storage, read_write> B: array<{{precision}}>; | ||
var<workgroup> tile: array<{{precision}}, {{BN}} * {{BM}}>; | ||
@compute @workgroup_size({{workgroupSize}}) | ||
fn main( | ||
@builtin(local_invocation_id) localID : vec3<u32>, | ||
@builtin(workgroup_id) groupID: vec3<u32>) { | ||
let bRow: u32 = groupID.x * {{BN}}; | ||
let bCol: u32 = groupID.y * {{BM}}; | ||
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let aPtr = bCol * {{N}} + bRow; | ||
let bPtr = bRow * {{M}} + bCol; | ||
let numThread: u32 = ({{BM}} * {{BN}}) / ({{TM}} * {{TN}}); | ||
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for (var resIdxM: u32 = 0; resIdxM < {{TM}}; resIdxM++) { | ||
for (var resIdxN: u32 = 0; resIdxN < {{TN}}; resIdxN++) { | ||
let idx: u32 = localID.x + numThread * (resIdxN + {{TN}} * resIdxM); | ||
let loadRow: u32 = idx / {{BN}}; | ||
let loadCol: u32 = idx % {{BN}}; | ||
tile[loadCol * {{BN}} + loadRow] = A[aPtr + loadRow * {{N}} + loadCol]; | ||
} | ||
} | ||
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workgroupBarrier(); | ||
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for (var resIdxN: u32 = 0; resIdxN < {{TN}}; resIdxN++) { | ||
for (var resIdxM: u32 = 0; resIdxM < {{TM}}; resIdxM++) { | ||
let idx: u32 = localID.x + numThread * (resIdxM + {{TM}} * resIdxN); | ||
let loadRow: u32 = idx / {{BM}}; | ||
let loadCol: u32 = idx % {{BM}}; | ||
B[bPtr + loadRow * {{M}} + loadCol] = tile[loadRow * {{BM}} + loadCol]; | ||
} | ||
} | ||
} | ||
)"; | ||
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inline KernelCode createTranspose2(const char *shaderTemplate, | ||
const size_t M, const size_t N, | ||
const size_t BM, const size_t BN, | ||
const size_t TM, const size_t TN, | ||
const Shape &workgroupSize = {256, 1, 1}, | ||
NumType precision = kf32) { | ||
assert(BM % TM == 0); | ||
assert(BN % TN == 0); | ||
assert(M % BM == 0); | ||
assert(N % BN == 0); | ||
std::string codeString(shaderTemplate); | ||
replaceAll(codeString, {{"{{workgroupSize}}", toString(workgroupSize)}, | ||
{"{{precision}}", toString(precision)}, | ||
{"{{M}}", toString(M)}, | ||
{"{{N}}", toString(N)}, | ||
{"{{BM}}", toString(BM)}, | ||
{"{{BN}}", toString(BN)}, | ||
{"{{TM}}", toString(TM)}, | ||
{"{{TN}}", toString(TN)} | ||
}); | ||
std::string unrolledCode = codeString ;// loopUnrolling(codeString); | ||
return {unrolledCode, workgroupSize}; | ||
} | ||
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void initData(size_t M, size_t N, std::unique_ptr<float[]> &inputPtr) { | ||
std::mt19937 gen(314159); | ||
randn(inputPtr.get(), M * N, gen); | ||
LOG(kDefLog, kInfo, "%s", show<float>(inputPtr.get(), M, N, "Input").c_str()); | ||
} | ||
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Kernel selectTranspose(Context &ctx, int version, | ||
const Bindings</* input, output */ 2> &bindings, | ||
size_t M, size_t N) { | ||
Kernel kernel; | ||
if (version == 1) { | ||
Shape wgSize = {16, 16, 1}; | ||
LOG(kDefLog, kInfo, "wgSize: %s", toString(wgSize).c_str()); | ||
KernelCode transpose = | ||
createTranspose1(kShaderTranspose1, M, N, /*wgsize*/ wgSize); // The shape of input == M x N | ||
kernel = createKernel(ctx, transpose, bindings, | ||
/*nWorkgroups*/ cdiv({N, M, 1}, wgSize)); // The shape of output == N x M | ||
} else if (version == 2) { | ||
static constexpr size_t BM = 64; | ||
static constexpr size_t BK = 16; | ||
static constexpr size_t BN = 64; | ||
static constexpr size_t TM = BM / BK; | ||
static constexpr size_t TN = BN / BK; | ||
Shape wgSize = {(BM / TM) * (BN / TN), 1, 1}; // This is the same as BK * BK. | ||
Shape nWorkgroups = {cdiv(N, BN), cdiv(M, BM), 1}; | ||
LOG(kDefLog, kInfo, "M: %d, N: %d", M, N); | ||
LOG(kDefLog, kInfo, "BM: %d, BK: %d, BN: %d, TM: %d, TN: %d", BM, BK, BN, TM, TN); | ||
LOG(kDefLog, kInfo, "wgSize: ( %s )", toString(wgSize).c_str()); | ||
LOG(kDefLog, kInfo, "nWorkgroups: ( %s )", toString(nWorkgroups).c_str()); | ||
KernelCode transpose = createTranspose2(kShaderTranspose2, M, N, BM, BN, TM, TN, | ||
/*wgSize*/ wgSize, | ||
kf32); | ||
kernel = createKernel(ctx, transpose, bindings, | ||
/*nWorkgroups*/ nWorkgroups); | ||
} else if (version == 0) { | ||
LOG(kDefLog, kInfo, "Skip Creating Kernel", M, N); | ||
} | ||
return kernel; | ||
} | ||
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void runTest(int version, size_t M, size_t N, | ||
std::unique_ptr<float[]> &inputPtr, | ||
std::unique_ptr<float[]> &outputPtr) { | ||
bool isCPU = version == 0; | ||
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// Allocate GPU buffers and copy data | ||
Context ctx = createContext(); | ||
Tensor input = createTensor(ctx, Shape{M, N}, kf32, inputPtr.get()); | ||
Tensor output = createTensor(ctx, Shape{N, M}, kf32); | ||
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constexpr size_t nIter = 50; | ||
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// Initialize Kernel and bind GPU buffers | ||
LOG(kDefLog, kInfo, "Creating Kernel"); | ||
Kernel kernel = selectTranspose(ctx, version, {input, output}, M, N); | ||
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// Dispatch kernel execution | ||
LOG(kDefLog, kInfo, "Dispatching Kernel version %d, %d iterations ...", | ||
version, nIter); | ||
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// pre-allocate promises and futures for async dispatch | ||
// TODO(avh): implement a pooling mechanism for promises/futures in gpu.h | ||
std::array<std::promise<void>, nIter> promises; | ||
std::array<std::future<void>, nIter> futures; | ||
for (int i = 0; i < nIter; i++) { | ||
futures[i] = promises[i].get_future(); | ||
} | ||
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// Dispatch kernel nIter times | ||
auto start = std::chrono::high_resolution_clock::now(); | ||
for (int i = 0; i < nIter; i++) { | ||
if (!isCPU) { | ||
dispatchKernel(ctx, kernel, promises[i]); | ||
wait(ctx, futures[i]); | ||
resetCommandBuffer(ctx.device, kernel); | ||
} else { | ||
transpose(inputPtr.get(), outputPtr.get(), M, N); | ||
} | ||
} | ||
auto end = std::chrono::high_resolution_clock::now(); | ||
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// Report performance. | ||
// Use microsecond for more accurate time measurement | ||
auto duration = | ||
std::chrono::duration_cast<std::chrono::microseconds>(end - start); | ||
float gbps = sizeof(float) * M * N / | ||
(static_cast<double>(duration.count()) / 1000000.0) / | ||
1000000000.0 * static_cast<float>(nIter); | ||
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LOG(kDefLog, kInfo, "Copying result to CPU"); | ||
if (!isCPU) { | ||
toCPU(ctx, output, outputPtr.get(), M * N * sizeof(float)); | ||
} | ||
LOG(kDefLog, kInfo, "%s", | ||
show<float>(outputPtr.get(), N, M, "Output").c_str()); | ||
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LOG(kDefLog, kInfo, "\n\n====================================================================" | ||
"============\nExecution Time: (M = %d, N = %d) x %d iterations " | ||
":\n%.3f " | ||
"milliseconds / dispatch ~ %.2f " | ||
"GB/s\n================================================================" | ||
"================\n\n", | ||
M, N, nIter, duration.count() / static_cast<double>(nIter) / 1000.0 /* us -> ms */, gbps); | ||
} | ||
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int main() { | ||
char* version_str = getenv("TEST_VERSION"); | ||
int version = version_str == NULL ? 2 : atoi(version_str); | ||
// 0 == cpu | ||
// 1 == naive transpose | ||
// 2 == tiling with shared memory | ||
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size_t M, N; // Matrix dimensions | ||
static constexpr int kTestSize = 2; | ||
if constexpr (kTestSize == 0) { | ||
// Tiny test | ||
M = 16; | ||
N = 32; | ||
} else if constexpr (kTestSize == 1) { | ||
// Small test | ||
M = 256; | ||
N = 512; | ||
} else { | ||
// Large test | ||
M = 4096; | ||
N = 2 * 4096; | ||
} | ||
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std::unique_ptr<float[]> inputPtr = std::make_unique<float[]>(M * N); | ||
std::unique_ptr<float[]> outputPtr = std::make_unique<float[]>(N * M); | ||
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initData(M, N, inputPtr); | ||
runTest(version, M, N, inputPtr, outputPtr); | ||
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LOG(kDefLog, kInfo, "Done."); | ||
return 0; | ||
} |
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