可以使用MPI_
Gpu
_numa_bind()将MPI进程绑定到特定的
GPU
,然后使用cudaMemcpyPeer()进行
GPU
之间的数据传输。
下面是一个示例代码,其中两个MPI进程都绑定到不同的
GPU
,并使用cudaMem
cp
yPeer()传输数据:
#include <mpi.h>
#include <cuda_runtime.h>
int main(int argc, char **argv) {
int rank, size;
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &size);
// Bind each MPI process to a specific GPU
int devId = rank % 2; // alternate between devices 0 and 1
cudaSetDevice(devId);
MPI_Gpu_numa_bind(devId);
// Allocate and initialize data on each GPU
int *data = (int*) malloc(1000 * sizeof(int));
for (int i = 0; i < 1000; i++) {
data[i] = rank; // each process's data is a different rank number
int *d_data;
cudaMalloc(&d_data, 1000 * sizeof(int));
cudaMemcpy(d_data, data, 1000 * sizeof(int), cudaMemcpyHostToDevice);
// Transfer data between GPUs using cudaMemcpyPeer()
if (rank == 0) {
cudaMemcpyPeer(d_data + 500, 1, d_data, 0, 500 * sizeof(int));
} else {
cudaMemcpyPeer(d_data, 0, d_data + 500, 1, 500 * sizeof(int));
// Check the result
cudaMemcpy(data, d_data, 1000 * sizeof(int), cudaMemcpyDeviceToHost);
if (rank == 0) {
for (int i = 0; i < 10; i++) {
printf("%d ", data[i]);
} else {
for (int i = 990; i < 1000; i++) {
printf("%d ", data[i]);
printf("\n");
// Cleanup
cudaFree(d_data);
free(data);
MPI_Finalize();
return 0;