mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-04-20 06:49:15 +00:00
Adding dispatcher architecture (#3300)
* WIP POC of dispatcher * Dispatcher python workflow setup. * Dispatcher cleanup and updates. Further dispatcher cleanup and updates. Build fixes Improvements and python to CK example Improvements to readme * Fixes to python paths * Cleaning up code * Improving dispatcher support for different arch Fixing typos * Fix formatting errors * Cleaning up examples * Improving codegeneration * Improving and fixing C++ examples * Adding conv functionality (fwd,bwd,bwdw) and examples. * Fixes based on feedback. * Further fixes based on feedback. * Adding stress test for autogeneration and autocorrection, and fixing preshuffle bug. * Another round of improvements based on feedback. * Trimming out unnecessary code. * Fixing the multi-D implementation. * Using gpu verification for gemms and fixing convolutions tflops calculation. * Fix counter usage issue and arch filtering per ops. * Adding changelog and other fixes. * Improve examples and resolve critical bugs. * Reduce build time for python examples. * Fixing minor bug. * Fix compilation error. * Improve installation instructions for dispatcher. * Add docker based installation instructions for dispatcher. * Fixing arch-based filtering to match tile engine. * Remove dead code and fix arch filtering. * Minor bugfix. * Updates after rebase. * Trimming code. * Fix copyright headers. * Consolidate examples, cut down code. * Minor fixes. * Improving python examples. * Update readmes. * Remove conv functionality. * Cleanup following conv removable.
This commit is contained in:
Vidyasagar Ananthan
committed by
GitHub
GitHub
parent
44f481a45c
commit
9e049a32a1
173
dispatcher/tests/test_real_kernel_performance.cpp
Normal file
173
dispatcher/tests/test_real_kernel_performance.cpp
Normal file
@@ -0,0 +1,173 @@
|
||||
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
|
||||
// SPDX-License-Identifier: MIT
|
||||
|
||||
/**
|
||||
* Performance test with real GPU kernel
|
||||
* Measures and reports detailed performance metrics
|
||||
*/
|
||||
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
#include <cmath>
|
||||
#include <memory>
|
||||
#include <hip/hip_runtime.h>
|
||||
|
||||
#include "ck_tile/dispatcher/dispatcher.hpp"
|
||||
#include "ck_tile/dispatcher/registry.hpp"
|
||||
#include "ck_tile/dispatcher/backends/generated_tile_backend.hpp"
|
||||
|
||||
// Kernel header included via -include compiler flag
|
||||
|
||||
using namespace ck_tile::dispatcher;
|
||||
using namespace ck_tile::dispatcher::backends;
|
||||
using Priority = ck_tile::dispatcher::Registry::Priority;
|
||||
|
||||
#define HIP_CHECK(call) \
|
||||
{ \
|
||||
hipError_t err = call; \
|
||||
if(err != hipSuccess) \
|
||||
{ \
|
||||
std::cerr << "HIP Error: " << hipGetErrorString(err) << "\n"; \
|
||||
exit(1); \
|
||||
} \
|
||||
}
|
||||
|
||||
int main()
|
||||
{
|
||||
std::cout << "=======================================\n";
|
||||
std::cout << "Performance Test - Real GPU Kernel\n";
|
||||
std::cout << "=======================================\n\n";
|
||||
|
||||
std::cout << "Kernel: " << KERNEL_NAME << "\n";
|
||||
std::cout << "Device: AMD Instinct MI325X (gfx942)\n\n";
|
||||
|
||||
// Register kernel
|
||||
KernelKey key;
|
||||
key.signature.dtype_a = DataType::FP16;
|
||||
key.signature.dtype_b = DataType::FP16;
|
||||
key.signature.dtype_c = DataType::FP16;
|
||||
key.signature.dtype_acc = DataType::FP32;
|
||||
key.signature.layout_a = LayoutTag::RowMajor;
|
||||
key.signature.layout_b = LayoutTag::ColMajor;
|
||||
key.signature.layout_c = LayoutTag::RowMajor;
|
||||
key.signature.transpose_a = false;
|
||||
key.signature.transpose_b = false;
|
||||
key.signature.grouped = false;
|
||||
key.signature.split_k = 1;
|
||||
key.signature.elementwise_op = "PassThrough";
|
||||
key.signature.num_d_tensors = 0;
|
||||
key.signature.structured_sparsity = false;
|
||||
|
||||
key.algorithm.tile_shape = {128, 128, 32};
|
||||
key.algorithm.wave_shape = {2, 2, 1};
|
||||
key.algorithm.warp_tile_shape = {32, 32, 16};
|
||||
key.algorithm.pipeline = Pipeline::CompV4;
|
||||
key.algorithm.scheduler = Scheduler::Intrawave;
|
||||
key.algorithm.epilogue = Epilogue::CShuffle;
|
||||
key.algorithm.block_size = 256;
|
||||
key.algorithm.double_buffer = true;
|
||||
key.algorithm.persistent = false;
|
||||
key.algorithm.preshuffle = false;
|
||||
key.algorithm.transpose_c = false;
|
||||
key.algorithm.num_wave_groups = 1;
|
||||
key.gfx_arch = "gfx942";
|
||||
|
||||
auto kernel =
|
||||
create_generated_tile_kernel<SelectedKernel, ADataType, BDataType, CDataType, AccDataType>(
|
||||
key, KERNEL_NAME);
|
||||
|
||||
Registry::instance().clear();
|
||||
Registry::instance().register_kernel(kernel, Priority::High);
|
||||
|
||||
Dispatcher dispatcher;
|
||||
|
||||
// Performance benchmark sizes
|
||||
std::vector<std::tuple<int, int, int, const char*>> benchmarks = {
|
||||
{128, 128, 128, "Tiny"},
|
||||
{256, 256, 256, "Small"},
|
||||
{512, 512, 512, "Medium"},
|
||||
{1024, 1024, 1024, "Large"},
|
||||
{2048, 2048, 2048, "Very Large"},
|
||||
};
|
||||
|
||||
std::cout << "Performance Benchmark Results\n";
|
||||
std::cout << "=============================\n\n";
|
||||
|
||||
std::cout << " Size | Time (ms) | TFLOPS | BW (GB/s) | Status\n";
|
||||
std::cout << " ----------|-----------|--------|-----------|--------\n";
|
||||
|
||||
bool all_passed = true;
|
||||
|
||||
for(const auto& [M, N, K, label] : benchmarks)
|
||||
{
|
||||
// Prepare data
|
||||
std::vector<ADataType> A_host(M * K, ADataType(1.0f));
|
||||
std::vector<BDataType> B_host(K * N, BDataType(1.0f));
|
||||
std::vector<CDataType> C_gpu(M * N);
|
||||
|
||||
ADataType *A_dev, *B_dev;
|
||||
CDataType* C_dev;
|
||||
|
||||
HIP_CHECK(hipMalloc(&A_dev, M * K * sizeof(ADataType)));
|
||||
HIP_CHECK(hipMalloc(&B_dev, K * N * sizeof(BDataType)));
|
||||
HIP_CHECK(hipMalloc(&C_dev, M * N * sizeof(CDataType)));
|
||||
|
||||
HIP_CHECK(
|
||||
hipMemcpy(A_dev, A_host.data(), M * K * sizeof(ADataType), hipMemcpyHostToDevice));
|
||||
HIP_CHECK(
|
||||
hipMemcpy(B_dev, B_host.data(), K * N * sizeof(BDataType), hipMemcpyHostToDevice));
|
||||
HIP_CHECK(hipMemset(C_dev, 0, M * N * sizeof(CDataType)));
|
||||
|
||||
// Execute
|
||||
Problem problem(M, N, K);
|
||||
float time_ms = dispatcher.run(A_dev, B_dev, C_dev, problem);
|
||||
|
||||
// Calculate metrics
|
||||
double flops = 2.0 * M * N * K;
|
||||
double tflops = (flops / (time_ms * 1e-3)) / 1e12;
|
||||
|
||||
// Bandwidth (A + B read, C write)
|
||||
double bytes = (M * K + K * N + M * N) * sizeof(CDataType);
|
||||
double bandwidth_gbs = (bytes / (time_ms * 1e-3)) / 1e9;
|
||||
|
||||
// Validate
|
||||
HIP_CHECK(hipMemcpy(C_gpu.data(), C_dev, M * N * sizeof(CDataType), hipMemcpyDeviceToHost));
|
||||
|
||||
int correct = 0;
|
||||
for(int i = 0; i < M * N; i++)
|
||||
{
|
||||
if(std::abs(float(C_gpu[i]) - float(K)) < 1.0f)
|
||||
correct++;
|
||||
}
|
||||
|
||||
bool passed = (correct == M * N);
|
||||
all_passed = all_passed && passed;
|
||||
|
||||
char size_label[32];
|
||||
snprintf(size_label, sizeof(size_label), "%s %d³", label, M);
|
||||
|
||||
printf(" %-9s | %9.4f | %6.2f | %9.1f | %s\n",
|
||||
size_label,
|
||||
time_ms,
|
||||
tflops,
|
||||
bandwidth_gbs,
|
||||
passed ? "[OK]" : "[FAIL]");
|
||||
|
||||
HIP_CHECK(hipFree(A_dev));
|
||||
HIP_CHECK(hipFree(B_dev));
|
||||
HIP_CHECK(hipFree(C_dev));
|
||||
}
|
||||
|
||||
std::cout << "\n";
|
||||
|
||||
if(all_passed)
|
||||
{
|
||||
std::cout << "[OK] ALL PERFORMANCE TESTS PASSED\n";
|
||||
return 0;
|
||||
}
|
||||
else
|
||||
{
|
||||
std::cout << "[FAIL] SOME TESTS FAILED\n";
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user