129 lines
3.9 KiB
Plaintext
129 lines
3.9 KiB
Plaintext
#include "matmul.h"
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#include "util.h"
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#include <cuda_runtime.h>
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#include <mpi.h>
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#define CUDA_CALL(f) \
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{ \
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cudaError_t err = (f); \
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if (err != cudaSuccess) { \
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fprintf(stderr, "CUDA error at [%s:%d] %d %s\n", __FILE__, __LINE__, \
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err, cudaGetErrorString(err)); \
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exit(1); \
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} \
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}
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#define MAX_NUM_GPU 4
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int num_devices = 0;
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__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)
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return;
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C[i * N + j] = 0;
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for (int k = 0; k < K; ++k) {
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C[i * N + j] += A[i * K + k] * B[k * N + j];
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}
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}
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static int mpi_rank, mpi_world_size;
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// Array of device (GPU) pointers
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static float *a_d[MAX_NUM_GPU];
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static float *b_d[MAX_NUM_GPU];
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static float *c_d[MAX_NUM_GPU];
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static int Mbegin[MAX_NUM_GPU], Mend[MAX_NUM_GPU];
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void matmul(const float *A, const float *B, float *C, int M, int N, int K) {
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// Upload A and B matrix to every GPU
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL(cudaMemcpy(a_d[i], A + Mbegin[i] * K,
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(Mend[i] - Mbegin[i]) * K * sizeof(float),
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cudaMemcpyHostToDevice));
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CUDA_CALL(
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cudaMemcpy(b_d[i], B, K * N * sizeof(float), cudaMemcpyHostToDevice));
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}
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// Launch kernel on every GPU
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for (int i = 0; i < num_devices; i++) {
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dim3 blockDim(1, 1, 1);
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dim3 gridDim(Mend[i] - Mbegin[i], N, 1);
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CUDA_CALL(cudaSetDevice(i));
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matmul_kernel<<<gridDim, blockDim>>>(a_d[i], b_d[i], c_d[i], M, N, K);
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}
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL(cudaDeviceSynchronize());
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}
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// Download C matrix from GPUs
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL(cudaMemcpy(C + Mbegin[i] * N, c_d[i],
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(Mend[i] - Mbegin[i]) * N * sizeof(float),
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cudaMemcpyDeviceToHost));
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}
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// DO NOT REMOVE; NEEDED FOR TIME MEASURE
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL(cudaDeviceSynchronize());
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}
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}
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void matmul_initialize(int M, int N, int K) {
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MPI_Comm_rank(MPI_COMM_WORLD, &mpi_rank);
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MPI_Comm_size(MPI_COMM_WORLD, &mpi_world_size);
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// Only root process do something
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if (mpi_rank == 0) {
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CUDA_CALL(cudaGetDeviceCount(&num_devices));
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printf("Using %d devices\n", num_devices);
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for (int i = 0; i < num_devices; i++) {
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cudaDeviceProp prop;
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CUDA_CALL(cudaGetDeviceProperties(&prop, i));
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// Try printing more detailed information here
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printf("GPU %d: %s\n", i, prop.name);
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}
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if (num_devices <= 0) {
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printf("No CUDA device found. Aborting\n");
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exit(1);
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}
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// Setup problem size for each GPU
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for (int i = 0; i < num_devices; i++) {
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Mbegin[i] = (M / num_devices) * i;
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Mend[i] = (M / num_devices) * (i + 1);
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}
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Mend[num_devices - 1] = M;
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// Allocate device memory for each GPU
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL(cudaSetDevice(i));
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CUDA_CALL(cudaMalloc(&a_d[i], (Mend[i] - Mbegin[i]) * K * sizeof(float)));
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CUDA_CALL(cudaMalloc(&b_d[i], K * N * sizeof(float)));
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CUDA_CALL(cudaMalloc(&c_d[i], (Mend[i] - Mbegin[i]) * N * sizeof(float)));
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}
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}
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}
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void matmul_finalize() {
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// Only root process do something
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if (mpi_rank == 0) {
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// Free all GPU memory
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for (int i = 0; i < num_devices; i++) {
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CUDA_CALL(cudaFree(a_d[i]));
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CUDA_CALL(cudaFree(b_d[i]));
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CUDA_CALL(cudaFree(c_d[i]));
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}
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}
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}
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