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157 lines
4.3 KiB
157 lines
4.3 KiB
//Patric Zhao: patric.zhao@gmail.com
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#include <chrono>
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#include <iostream>
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#include <CL/sycl.hpp>
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#define random_float() (rand() / double(RAND_MAX))
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using namespace std;
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using namespace sycl;
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// return execution time
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double gpu_kernel(float *A, float *B, float *C, int M, int N, int K, int block_size, sycl::queue &q) {
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// define the workgroup size and mapping
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auto grid_rows = (M + block_size - 1) / block_size * block_size;
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auto grid_cols = (N + block_size - 1) / block_size * block_size;
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auto local_ndrange = range<2>(block_size, block_size);
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auto global_ndrange = range<2>(grid_rows, grid_cols);
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double duration = 0.0f;
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auto e = q.submit([&](sycl::handler &h) {
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h.parallel_for<class k_name_t>(
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sycl::nd_range<2>(global_ndrange, local_ndrange), [=](sycl::nd_item<2> index) {
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int row = index.get_global_id(0);
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int col = index.get_global_id(1);
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float sum = 0.0f;
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for (int i = 0; i < K; i++) {
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sum += A[row * K + i] * B[i * N + col];
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}
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C[row * N + col] = sum;
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});
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});
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e.wait();
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duration += (e.get_profiling_info<info::event_profiling::command_end>() -
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e.get_profiling_info<info::event_profiling::command_start>()) /1000.0f/1000.0f;
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return(duration);
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}
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// return execution time
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double cpu_kernel(float *cA, float *cB, float *cC, int M, int N, int K) {
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double duration = 0.0;
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std::chrono::high_resolution_clock::time_point s, e;
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// Single Thread Computation in CPU
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s = std::chrono::high_resolution_clock::now();
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for(int i = 0; i < M; i++) {
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for(int j = 0; j < N; j++) {
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float sum = 0.0f;
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for(int k = 0; k < K; k++) {
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sum += cA[i * K + k] * cB[k * N + j];
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}
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cC[i * N + j] = sum;
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}
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}
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e = std::chrono::high_resolution_clock::now();
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duration = std::chrono::duration<float, std::milli>(e - s).count();
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return(duration);
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}
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int verify(float *cpu_res, float *gpu_res, int length){
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int err = 0;
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for(int i = 0; i < length; i++) {
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if( fabs(cpu_res[i] - gpu_res[i]) > 1e-3) {
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err++;
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printf("\n%lf, %lf", cpu_res[i], gpu_res[i]);
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}
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}
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return(err);
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}
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int gemm(const int M,
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const int N,
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const int K,
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const int block_size,
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const int iterations,
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sycl::queue &q) {
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cout << "Problem size: c(" << M << "," << N << ") ="
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<< " a(" << M << "," << K << ") *"
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<< " b(" << K << "," << N << ")\n";
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auto A = malloc_shared<float>(M * K, q);
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auto B = malloc_shared<float>(K * N, q);
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auto C = malloc_shared<float>(M * N, q);
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auto C_host = malloc_host<float>(M * N, q);
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// init the A/B/C
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for(int i=0; i < M * K; i++) {
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A[i] = random_float();
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}
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for(int i=0; i < K * N; i++) {
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B[i] = random_float();
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}
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for(int i=0; i < M * N; i++) {
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C[i] = 0.0f;
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C_host[i] = 0.0f;
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}
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double flopsPerMatrixMul
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= 2.0 * static_cast<double>(M) * static_cast<double>(N) * static_cast<double>(K);
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double duration_gpu = 0.0f;
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double duration_cpu = 0.0f;
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// GPU compuation and timer
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int warmup = 10;
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for (int run = 0; run < iterations + warmup; run++) {
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float duration = gpu_kernel(A, B, C, M, N, K, block_size, q);
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if(run >= warmup) duration_gpu += duration;
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}
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duration_gpu = duration_gpu / iterations;
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// CPU compuation and timer
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warmup = 2;
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for(int run = 0; run < iterations/2 + warmup; run++) {
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float duration = cpu_kernel(A, B, C_host, M, N, K);
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if(run >= warmup) duration_cpu += duration;
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}
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duration_cpu = duration_cpu / iterations/2;
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// Compare the resutls of CPU and GPU
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int errCode = 0;
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errCode = verify(C_host, C, M*N);
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if(errCode > 0) printf("\nThere are %d errors\n", errCode);
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printf("\nPerformance Flops = %lf, \n"
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"GPU Computation Time = %lf (ms); \n"
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"CPU Computaiton Time = %lf (ms); \n",
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flopsPerMatrixMul, duration_gpu, duration_cpu);
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free(A, q);
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free(B, q);
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free(C, q);
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free(C_host, q);
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return(errCode);
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}
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int main() {
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auto propList = cl::sycl::property_list {cl::sycl::property::queue::enable_profiling()};
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queue my_gpu_queue( cl::sycl::gpu_selector{} , propList);
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int errCode = gemm(1024, 1024, 1024, 4, 10, my_gpu_queue);
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return(errCode);
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}
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