105 lines
3.6 KiB
Plaintext
105 lines
3.6 KiB
Plaintext
#include <cstdio>
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#include "matmul.h"
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#define CHECK_CUDA(call) \
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do { \
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cudaError_t status_ = call; \
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if (status_ != cudaSuccess) { \
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fprintf(stderr, "CUDA error (%s:%d): %s\n", __FILE__, __LINE__, \
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cudaGetErrorString(status_)); \
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exit(EXIT_FAILURE); \
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} \
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} while (0)
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static __global__ void matmul_kernel(float *A, float *B, float *C, int M, int N,
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int K) {
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int i = blockDim.x * blockIdx.x + threadIdx.x;
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int j = blockDim.y * blockIdx.y + threadIdx.y;
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if (i >= M || j >= N) return;
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float sum = 0.0;
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for (int k = 0; k < K; ++k) sum += A[i * K + k] * B[k * N + j];
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C[i * N + j] = sum;
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}
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#define NGPU 4
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#define EVENTS_PER_GPU 1 // Increase as needed
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static size_t Mbegin[NGPU], Mend[NGPU];
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static size_t ngpu;
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static cudaStream_t streams[NGPU];
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static cudaEvent_t events[NGPU][EVENTS_PER_GPU];
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static float *A_gpu[NGPU], *B_gpu[NGPU], *C_gpu[NGPU];
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void matmul_multigpu_initialize(size_t M, size_t N, size_t K) {
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ngpu = 4;
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for (size_t i = 0; i < ngpu; i++) {
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Mbegin[i] = M / ngpu * i;
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Mend[i] = M / ngpu * (i + 1);
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if (i == ngpu - 1) Mend[i] = M;
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}
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for (size_t i = 0; i < ngpu; i++) {
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CHECK_CUDA(cudaSetDevice(i));
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CHECK_CUDA(cudaStreamCreate(&streams[i]));
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for (int j = 0; j < EVENTS_PER_GPU; j++) {
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CHECK_CUDA(cudaEventCreate(&events[i][j]));
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}
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}
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for (size_t i = 0; i < ngpu; i++) {
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CHECK_CUDA(cudaSetDevice(i));
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CHECK_CUDA(
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cudaMalloc(&A_gpu[i], (Mend[i] - Mbegin[i]) * K * sizeof(float)));
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CHECK_CUDA(cudaMalloc(&B_gpu[i], K * N * sizeof(float)));
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CHECK_CUDA(
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cudaMalloc(&C_gpu[i], (Mend[i] - Mbegin[i]) * N * sizeof(float)));
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}
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}
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void matmul_multigpu(float *A, float *B, float *C, size_t M, size_t N,
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size_t K) {
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for (size_t i = 0; i < ngpu; i++) {
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CHECK_CUDA(cudaSetDevice(i));
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CHECK_CUDA(cudaMemcpyAsync(A_gpu[i], &A[Mbegin[i] * K],
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(Mend[i] - Mbegin[i]) * K * sizeof(float),
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cudaMemcpyHostToDevice, streams[i]));
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CHECK_CUDA(cudaMemcpyAsync(B_gpu[i], B, K * N * sizeof(float),
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cudaMemcpyHostToDevice, streams[i]));
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}
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for (size_t i = 0; i < ngpu; i++) {
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CHECK_CUDA(cudaSetDevice(i));
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dim3 blockDim(32, 32);
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dim3 gridDim((Mend[i] - Mbegin[i] + 32 - 1) / 32, (N + 32 - 1) / 32);
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matmul_kernel<<<gridDim, blockDim, 0, streams[i]>>>(
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A_gpu[i], B_gpu[i], C_gpu[i], Mend[i] - Mbegin[i], N, K);
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CHECK_CUDA(cudaGetLastError());
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}
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for (size_t i = 0; i < ngpu; i++) {
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CHECK_CUDA(cudaSetDevice(i));
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CHECK_CUDA(cudaMemcpyAsync(&C[Mbegin[i] * N], C_gpu[i],
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(Mend[i] - Mbegin[i]) * N * sizeof(float),
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cudaMemcpyDeviceToHost, streams[i]));
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}
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for (size_t i = 0; i < ngpu; i++) {
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cudaSetDevice(i);
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cudaStreamSynchronize(streams[i]);
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}
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}
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void matmul_multigpu_finalize(size_t M, size_t N, size_t K) {
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for (size_t i = 0; i < ngpu; i++) {
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CHECK_CUDA(cudaSetDevice(i));
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CHECK_CUDA(cudaFree(A_gpu[i]));
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CHECK_CUDA(cudaFree(B_gpu[i]));
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CHECK_CUDA(cudaFree(C_gpu[i]));
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CHECK_CUDA(cudaStreamDestroy(streams[i]));
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for (int j = 0; j < EVENTS_PER_GPU; j++) {
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CHECK_CUDA(cudaEventDestroy(events[i][j]));
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}
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}
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} |