forked from jiuyuan/InfiniTensor
110 lines
3.1 KiB
C++
110 lines
3.1 KiB
C++
#ifdef INFINI_USE_NCCL
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#include "core/graph.h"
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#include "core/runtime.h"
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#include "cuda/cuda_runtime.h"
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#include "cuda/cuda_utility.h"
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#include "operators/all_reduce.h"
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#include "test.h"
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#include <nccl.h>
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#include <thread>
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static int WORLD_SIZE = 2;
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namespace infini {
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template <typename OperatorObj>
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void allReduce(const string taskName, int deviceID, vector<float> data,
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vector<float> ans) {
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// Create Runtimes and initiate communication
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Runtime cpuRuntime = NativeCpuRuntimeObj::getInstance();
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Runtime cudaRuntime = make_ref<CudaRuntimeObj>(deviceID);
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cudaRuntime->initComm(taskName, WORLD_SIZE, deviceID);
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// Create Graph and insert allReduce operation
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Graph g = make_ref<GraphObj>(cudaRuntime);
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auto input =
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g->addTensor(Shape{static_cast<int>(data.size())}, DataType::Float32);
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auto op = g->addOp<OperatorObj>(input, nullptr);
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// Copy data from CPU to GPU
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g->dataMalloc();
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input->copyin(data);
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// Run operation
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cudaRuntime->run(g);
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// Copy output from GPU to CPU
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auto result = op->getOutput()->clone(cpuRuntime);
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EXPECT_TRUE(result->equalData(ans));
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}
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TEST(CUDA_AllReduce, sum) {
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vector<float> data[2] = {{2., 3.}, {5., 6.}};
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vector<float> ans = {7., 9.};
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std::vector<std::thread> threads;
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for (int gpu = 0; gpu < WORLD_SIZE; ++gpu) {
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threads.emplace_back(allReduce<AllReduceSumObj>, "test_allreduce_sum",
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gpu, data[gpu], ans);
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}
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for (auto &thread : threads) {
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thread.join();
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}
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}
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TEST(CUDA_AllReduce, prod) {
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vector<float> data[2] = {{2., 3.}, {5., 6.}};
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vector<float> ans = {10., 18.};
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std::vector<std::thread> threads;
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for (int gpu = 0; gpu < WORLD_SIZE; ++gpu) {
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threads.emplace_back(allReduce<AllReduceProdObj>, "test_allreduce_prod",
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gpu, data[gpu], ans);
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}
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for (auto &thread : threads) {
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thread.join();
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}
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}
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TEST(CUDA_AllReduce, min) {
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vector<float> data[2] = {{2., 3.}, {5., 6.}};
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vector<float> ans = {2., 3.};
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std::vector<std::thread> threads;
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for (int gpu = 0; gpu < WORLD_SIZE; ++gpu) {
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threads.emplace_back(allReduce<AllReduceMinObj>, "test_allreduce_min",
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gpu, data[gpu], ans);
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}
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for (auto &thread : threads) {
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thread.join();
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}
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}
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TEST(CUDA_AllReduce, max) {
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vector<float> data[2] = {{2., 3.}, {5., 6.}};
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vector<float> ans = {5., 6.};
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std::vector<std::thread> threads;
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for (int gpu = 0; gpu < WORLD_SIZE; ++gpu) {
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threads.emplace_back(allReduce<AllReduceMaxObj>, "test_allreduce_max",
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gpu, data[gpu], ans);
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}
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for (auto &thread : threads) {
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thread.join();
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}
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}
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TEST(CUDA_AllReduce, avg) {
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vector<float> data[2] = {{2., 3.}, {5., 6.}};
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vector<float> ans = {3.5, 4.5};
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std::vector<std::thread> threads;
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for (int gpu = 0; gpu < WORLD_SIZE; ++gpu) {
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threads.emplace_back(allReduce<AllReduceAvgObj>, "test_allreduce_avg",
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gpu, data[gpu], ans);
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}
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for (auto &thread : threads) {
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thread.join();
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}
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}
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} // namespace infini
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#endif
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