mirror of
https://github.com/NVIDIA/cuda-samples.git
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129 lines
4.1 KiB
C++
129 lines
4.1 KiB
C++
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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/* Simple example demonstrating how to use MPI with CUDA
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*
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* Generate some random numbers on one node.
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* Dispatch them to all nodes.
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* Compute their square root on each node's GPU.
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* Compute the average of the results using MPI.
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*
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* simpleMPI.cpp: main program, compiled with mpicxx on linux/Mac platforms
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* on Windows, please download the Microsoft HPC Pack SDK 2008
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*/
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// MPI include
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#include <mpi.h>
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// System includes
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#include <iostream>
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using std::cout;
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using std::cerr;
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using std::endl;
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// User include
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#include "simpleMPI.h"
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// Error handling macros
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#define MPI_CHECK(call) \
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if ((call) != MPI_SUCCESS) { \
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cerr << "MPI error calling \"" #call "\"\n"; \
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my_abort(-1); \
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}
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// Host code
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// No CUDA here, only MPI
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int main(int argc, char *argv[]) {
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// Dimensions of the dataset
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int blockSize = 256;
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int gridSize = 10000;
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int dataSizePerNode = gridSize * blockSize;
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// Initialize MPI state
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MPI_CHECK(MPI_Init(&argc, &argv));
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// Get our MPI node number and node count
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int commSize, commRank;
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MPI_CHECK(MPI_Comm_size(MPI_COMM_WORLD, &commSize));
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MPI_CHECK(MPI_Comm_rank(MPI_COMM_WORLD, &commRank));
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// Generate some random numbers on the root node (node 0)
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int dataSizeTotal = dataSizePerNode * commSize;
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float *dataRoot = NULL;
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// Are we the root node?
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if (commRank == 0) {
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cout << "Running on " << commSize << " nodes" << endl;
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dataRoot = new float[dataSizeTotal];
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initData(dataRoot, dataSizeTotal);
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}
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// Allocate a buffer on each node
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float *dataNode = new float[dataSizePerNode];
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// Dispatch a portion of the input data to each node
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MPI_CHECK(MPI_Scatter(dataRoot, dataSizePerNode, MPI_FLOAT, dataNode,
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dataSizePerNode, MPI_FLOAT, 0, MPI_COMM_WORLD));
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if (commRank == 0) {
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// No need for root data any more
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delete[] dataRoot;
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}
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// On each node, run computation on GPU
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computeGPU(dataNode, blockSize, gridSize);
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// Reduction to the root node, computing the sum of output elements
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float sumNode = sum(dataNode, dataSizePerNode);
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float sumRoot;
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MPI_CHECK(
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MPI_Reduce(&sumNode, &sumRoot, 1, MPI_FLOAT, MPI_SUM, 0, MPI_COMM_WORLD));
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if (commRank == 0) {
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float average = sumRoot / dataSizeTotal;
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cout << "Average of square roots is: " << average << endl;
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}
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// Cleanup
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delete[] dataNode;
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MPI_CHECK(MPI_Finalize());
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if (commRank == 0) {
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cout << "PASSED\n";
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}
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return 0;
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}
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// Shut down MPI cleanly if something goes wrong
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void my_abort(int err) {
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cout << "Test FAILED\n";
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MPI_Abort(MPI_COMM_WORLD, err);
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}
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