#include "mat_mul.h" #include #include #define CUDA_CALL(f) \ { \ cudaError_t err = (f); \ if (err != cudaSuccess) { \ fprintf(stderr, "CUDA error at [%s:%d] %d %s\n", __FILE__, __LINE__, \ err, cudaGetErrorString(err)); \ exit(1); \ } \ } #define MAX_NUM_GPU 4 int num_devices = 0; __global__ void sgemm(float *A, float *B, float *C, int M, int N, int K) { int i = blockDim.x * blockIdx.x + threadIdx.x; int j = blockDim.y * blockIdx.y + threadIdx.y; if (i >= M || j >= N) return; float acc = 0; //for (int k = 0; k < K; ++k) { // acc += A[i * K + k] * B[k * N + j]; //} static int K_split = 128*2; for (int kk = 0; kk < K; kk+=K_split) { for (int k = kk; k < min(kk + K_split, K); k++) { acc += A[i * K + k] * B[k * N + j]; } } C[i * N + j] = acc; } // Array of device (GPU) pointers static float *a_d[MAX_NUM_GPU]; static float *b_d[MAX_NUM_GPU]; static float *c_d[MAX_NUM_GPU]; static int M, N, K; static int Mbegin[MAX_NUM_GPU], Mend[MAX_NUM_GPU]; void mat_mul(float *_A, float *_B, float *_C, int _M, int _N, int _K) { // Launch kernel on every GPU for (int i = 0; i < num_devices; i++) { static int M_block = 2; static int N_block = 128; int M_grid = ((Mend[i] - Mbegin[i]) + (M_block - 1)) / M_block; int N_grid = (N + N_block - 1)/N_block; //printf("[GPU %d] M:%d, M_block:%d, M_grid:%d\n", i, Mend[i] - Mbegin[i], M_block, M_grid); //dim3 blockDim(1, 1, 1); dim3 blockDim(M_block, N_block, 1); dim3 gridDim(M_grid, N_grid, 1); CUDA_CALL( cudaSetDevice(i) ); sgemm<<>>(a_d[i], b_d[i], c_d[i], (Mend[i] - Mbegin[i]), N, K); } // DO NOT REMOVE; NEEDED FOR TIME MEASURE for (int i = 0; i < num_devices; i++) { CUDA_CALL( cudaDeviceSynchronize() ); } } void mat_mul_init(float *A, float *B, float *C, int _M, int _N, int _K) { M = _M, N = _N, K = _K; CUDA_CALL( cudaGetDeviceCount(&num_devices) ); printf("Using %d devices\n", num_devices); for (int i = 0; i < num_devices; i++) { cudaDeviceProp prop; CUDA_CALL( cudaGetDeviceProperties(&prop, i) ); // Try printing more detailed information here printf("[GPU %d] %s\n", i, prop.name); } if (num_devices <= 0) { printf("No CUDA device found. Aborting\n"); exit(1); } // Setup problem size for each GPU for (int i = 0; i < num_devices; i++) { Mbegin[i] = (M / num_devices) * i; Mend[i] = (M / num_devices) * (i + 1); } Mend[num_devices - 1] = M; // Allocate device memory for each GPU for (int i = 0; i < num_devices; i++) { CUDA_CALL( cudaSetDevice(i) ); CUDA_CALL( cudaMalloc(&a_d[i], (Mend[i] - Mbegin[i]) * K * sizeof(float)) ); CUDA_CALL( cudaMalloc(&b_d[i], K * N * sizeof(float)) ); CUDA_CALL( cudaMalloc(&c_d[i], (Mend[i] - Mbegin[i]) * N * sizeof(float)) ); } // Upload A and B matrix to every GPU for (int i = 0; i < num_devices; i++) { CUDA_CALL( cudaMemcpy(a_d[i], A + Mbegin[i] * K, (Mend[i] - Mbegin[i]) * K * sizeof(float), cudaMemcpyHostToDevice) ); CUDA_CALL( cudaMemcpy(b_d[i], B, K * N * sizeof(float), cudaMemcpyHostToDevice) ); } // DO NOT REMOVE; NEEDED FOR TIME MEASURE for (int i = 0; i < num_devices; i++) { CUDA_CALL( cudaDeviceSynchronize() ); } } void mat_mul_final(float *A, float *B, float *C, int M, int N, int K) { // Do any post-matmul cleanup work here. // Download C matrix from GPUs for (int i = 0; i < num_devices; i++) { CUDA_CALL( cudaMemcpy(C + Mbegin[i] * N, c_d[i], (Mend[i] - Mbegin[i]) * N * sizeof(float), cudaMemcpyDeviceToHost) ); } // DO NOT REMOVE; NEEDED FOR TIME MEASURE for (int i = 0; i < num_devices; i++) { CUDA_CALL( cudaDeviceSynchronize() ); } }