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340 lines
8.8 KiB
340 lines
8.8 KiB
/*
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* ===========================================================================
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*
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* Filename: mpi_daxpy_nvtx.c
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*
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* Description: Adds MPI to cublas test, to debug issue on Summit
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*
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* Version: 1.0
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* Created: 05/20/2019 10:33:30 AM
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* Revision: none
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* Compiler: gcc
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*
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* Author: YOUR NAME (),
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* Organization:
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*
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* ===========================================================================
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*/
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#include <mpi.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include "cublas_v2.h"
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#include "cuda_runtime_api.h"
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#include "nvToolsExt.h"
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#include "cuda_profiler_api.h"
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#define GPU_CHECK_CALLS
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#include "cuda_error.h"
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// column major
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#define IDX2C(i,j,ld) (((j)*(ld))+(i))
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#define BARRIER
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static cublasHandle_t handle;
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static const int MB = 1024*1024;
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void set_rank_device(int n_ranks, int rank) {
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int n_devices, device, ranks_per_device;
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size_t memory_per_rank;
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cudaDeviceProp device_prop;
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CHECK("get device count", cudaGetDeviceCount(&n_devices));
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if (n_ranks > n_devices) {
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if (n_ranks % n_devices != 0) {
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printf("ERROR: Number of ranks (%d) not a multiple of number of GPUs (%d)\n",
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n_ranks, n_devices);
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exit(EXIT_FAILURE);
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}
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ranks_per_device = n_ranks / n_devices;
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device = rank / ranks_per_device;
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} else {
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ranks_per_device = 1;
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device = rank;
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}
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CHECK("get device props", cudaGetDeviceProperties(&device_prop, device));
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memory_per_rank = device_prop.totalGlobalMem / ranks_per_device;
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printf("RANK[%d/%d] => DEVICE[%d/%d] mem=%zd\n", rank+1, n_ranks,
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device+1, n_devices, memory_per_rank);
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CHECK("set device", cudaSetDevice(device));
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}
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int get_node_count(int n_ranks) {
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int shm_size;
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MPI_Comm shm_comm;
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MPI_Comm_split_type(MPI_COMM_WORLD, MPI_COMM_TYPE_SHARED, 0,
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MPI_INFO_NULL, &shm_comm);
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MPI_Comm_size(shm_comm, &shm_size);
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MPI_Comm_free(&shm_comm);
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return n_ranks / shm_size;
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}
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int main(int argc, char **argv) {
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const int n_per_node = 48*MB;
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int nodes = 1;
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int nall = n_per_node;
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int n = 0;
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int world_size, world_rank;
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size_t free_mem, total_mem;
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double a = 2.0;
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double sum = 0.0;
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double start_time = 0.0;
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double end_time = 0.0;
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double k_start_time = 0.0;
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double k_end_time = 0.0;
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double g_start_time = 0.0;
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double g_end_time = 0.0;
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double b_start_time = 0.0;
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double b_end_time = 0.0;
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#ifndef MANAGED
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double *h_x, *h_y;
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double *h_allx, *h_ally;
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#endif
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double *d_x, *d_y;
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double *d_allx, *d_ally;
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char *mb_per_core;
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MPI_Init(NULL, NULL);
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MPI_Comm_size(MPI_COMM_WORLD, &world_size);
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MPI_Comm_rank(MPI_COMM_WORLD, &world_rank);
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nodes = get_node_count(world_size);
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// hack: assume max 6 mpi per node, so we use bigger
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// arrays on multi-node runs
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/*
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if (world_size > 6) {
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nodes = (world_size + 5) / 6;
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}
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*/
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nall = nodes * n_per_node;
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n = nall / world_size;
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if (world_rank == 0) {
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printf("%d nodes, %d ranks, %d elements each, total %d\n",
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nodes, world_size, n, nall);
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}
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/*
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x = (double *)malloc(n*sizeof(*x));
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if (x == NULL) {
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printf("host malloc(x) failed\n");
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return EXIT_FAILURE;
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}
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y = (double *)malloc(n*sizeof(*y));
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if (y == NULL) {
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printf("host malloc(y) failed\n");
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return EXIT_FAILURE;
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}
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*/
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// DEBUG weirdness on summit where GENE can't see MEMORY_PER_CORE,
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// possibly because the system spectrum mpi uses it in some way.
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if (world_rank == 0) {
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mb_per_core = getenv("MEMORY_PER_CORE");
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if (mb_per_core == NULL) {
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printf("MEMORY_PER_CORE is not set\n");
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} else {
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printf("MEMORY_PER_CORE=%s\n", mb_per_core);
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}
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}
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set_rank_device(world_size, world_rank);
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//CHECK("setDevice", cudaSetDevice(0));
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cudaProfilerStart();
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start_time = MPI_Wtime();
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CHECK( "cublas", cublasCreate(&handle) );
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/*
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CHECK( "d_x", cudaMalloc((void**)&d_x, n*sizeof(*d_x)) );
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CHECK( "d_y", cudaMalloc((void**)&d_y, n*sizeof(*d_y)) );
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*/
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nvtxRangePushA("allocateArrays");
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#ifdef MANAGED
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CHECK( "d_x", cudaMallocManaged((void**)&d_x, n*sizeof(*d_x)) );
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CHECK( "d_y", cudaMallocManaged((void**)&d_y, n*sizeof(*d_y)) );
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CHECK( "d_allx", cudaMallocManaged((void**)&d_allx,
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n*sizeof(*d_allx)*world_size) );
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CHECK( "d_ally", cudaMallocManaged((void**)&d_ally,
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n*sizeof(*d_ally)*world_size) );
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#else
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CHECK( "h_x", cudaMallocHost((void**)&h_x, n*sizeof(*h_x)) );
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CHECK( "h_y", cudaMallocHost((void**)&h_y, n*sizeof(*h_y)) );
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CHECK( "d_x", cudaMalloc((void**)&d_x, n*sizeof(*d_x)) );
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CHECK( "d_y", cudaMalloc((void**)&d_y, n*sizeof(*d_y)) );
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CHECK( "d_allx", cudaMalloc((void**)&d_allx,
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n*sizeof(*d_allx)*world_size) );
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CHECK( "d_ally", cudaMalloc((void**)&d_ally,
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n*sizeof(*d_ally)*world_size) );
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CHECK( "h_allx", cudaMallocHost((void**)&h_allx,
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n*sizeof(*h_allx)*world_size) );
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CHECK( "h_ally", cudaMallocHost((void**)&h_ally,
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n*sizeof(*h_ally)*world_size) );
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#endif
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nvtxRangePop();
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if (world_rank == 0) {
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CHECK( "memInfo", cudaMemGetInfo(&free_mem, &total_mem) );
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printf("GPU memory %0.3f / %0.3f (%0.3f) MB\n", free_mem/(double)MB,
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(double)total_mem/MB, (double)(total_mem-free_mem)/MB);
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}
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nvtxRangePushA("initializeArrays");
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#ifdef MANAGED
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for (int i=0; i<n; i++) {
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d_x[i] = (i+1)/(double)n;
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d_y[i] = -d_x[i];
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}
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#else
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for (int i=0; i<n; i++) {
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h_x[i] = (i+1)/(double)n;
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h_y[i] = -h_x[i];
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}
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nvtxRangePushA("copyInput");
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CHECK("d_x = h_x",
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cudaMemcpy(d_x, h_x, n*sizeof(*h_x), cudaMemcpyHostToDevice) );
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CHECK("d_y = h_y",
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cudaMemcpy(d_y, h_y, n*sizeof(*h_y), cudaMemcpyHostToDevice) );
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nvtxRangePop();
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#endif
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nvtxRangePop();
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//MEMINFO("d_x", d_x, sizeof(d_x));
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//MEMINFO("d_y", d_y, sizeof(d_y));
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//MEMINFO("x", x, sizeof(x));
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//MEMINFO("y", y, sizeof(y));
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MEMINFO("d_x", d_x, sizeof(d_x));
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MEMINFO("d_y", d_y, sizeof(d_y));
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#ifndef MANAGED
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MEMINFO("h_x", h_x, sizeof(h_x));
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MEMINFO("h_y", h_y, sizeof(h_y));
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MEMINFO("h_allx", h_allx, sizeof(h_allx));
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MEMINFO("h_ally", h_ally, sizeof(h_ally));
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#endif
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k_start_time = MPI_Wtime();
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nvtxRangePushA("cublasDaxpy");
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CHECK("daxpy",
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cublasDaxpy(handle, n, &a, d_x, 1, d_y, 1) );
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CHECK("daxpy sync", cudaDeviceSynchronize());
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nvtxRangePop();
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k_end_time = MPI_Wtime();
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nvtxRangePushA("localSum");
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#ifdef MANAGED
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sum = 0.0;
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for (int i=0; i<n; i++) {
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sum += d_y[i];
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}
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#else
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nvtxRangePushA("copyOutput");
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CHECK("h_y = d_y",
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cudaMemcpy(h_y, d_y, n*sizeof(*h_y), cudaMemcpyDeviceToHost) );
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nvtxRangePop();
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sum = 0.0;
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for (int i=0; i<n; i++) {
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sum += h_y[i];
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}
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#endif
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nvtxRangePop();
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printf("%d/%d SUM = %f\n", world_rank, world_size, sum);
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#ifdef BARRIER
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b_start_time = MPI_Wtime();
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nvtxRangePushA("mpiBarrier");
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MPI_Barrier(MPI_COMM_WORLD);
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nvtxRangePop();
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b_end_time = MPI_Wtime();
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#endif
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g_start_time = MPI_Wtime();
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nvtxRangePushA("mpiAllGather");
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nvtxRangePushA("x");
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MPI_Allgather(d_x, n, MPI_DOUBLE, d_allx, n, MPI_DOUBLE, MPI_COMM_WORLD);
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nvtxRangePop();
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nvtxRangePushA("y");
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MPI_Allgather(d_y, n, MPI_DOUBLE, d_ally, n, MPI_DOUBLE, MPI_COMM_WORLD);
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nvtxRangePop();
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nvtxRangePop();
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g_end_time = MPI_Wtime();
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sum = 0.0;
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nvtxRangePushA("allSum");
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#ifdef MANAGED
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for (int i=0; i<n*world_size; i++) {
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sum += d_ally[i];
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}
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#else
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nvtxRangePushA("copyAlly");
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CHECK("h_ally = d_ally",
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cudaMemcpy(h_ally, d_ally, n*sizeof(*h_ally)*world_size,
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cudaMemcpyDeviceToHost) );
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nvtxRangePop();
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for (int i=0; i<n*world_size; i++) {
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sum += h_ally[i];
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}
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#endif
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nvtxRangePop();
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printf("%d/%d ALLSUM = %f\n", world_rank, world_size, sum);
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// cleanup
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nvtxRangePushA("free");
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#ifndef MANAGED
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cudaFreeHost(h_x);
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cudaFreeHost(h_y);
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cudaFreeHost(h_allx);
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cudaFreeHost(h_ally);
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#endif
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cudaFree(d_x);
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cudaFree(d_y);
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cudaFree(d_allx);
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cudaFree(d_ally);
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nvtxRangePop();
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end_time = MPI_Wtime();
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cudaProfilerStop();
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cublasDestroy(handle);
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MPI_Finalize();
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printf("%d/%d TIME total : %0.3f\n", world_rank, world_size,
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end_time-start_time);
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printf("%d/%d TIME kernel : %0.3f\n", world_rank, world_size,
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k_end_time-k_start_time);
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printf("%d/%d TIME barrier: %0.3f\n", world_rank, world_size,
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b_end_time-b_start_time);
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printf("%d/%d TIME gather : %0.3f\n", world_rank, world_size,
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g_end_time-g_start_time);
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return EXIT_SUCCESS;
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}
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