InfiniTensor/test/kernels/kunlun/test_kunlun_allgather.cc

51 lines
1.6 KiB
C++

#ifdef INFINI_USE_XCCL
#include "core/graph.h"
#include "core/runtime.h"
#include "kunlun/kunlun_runtime.h"
#include "operators/all_gather.h"
#include "test.h"
#include "xpu/bkcl.h"
#include <thread>
static int WORLD_SIZE = 2;
namespace infini {
void allGather(const string taskName, int deviceID, vector<float> data,
vector<vector<float>> ans) {
// Create Runtimes and initiate communication
Runtime cpuRuntime = NativeCpuRuntimeObj::getInstance();
Runtime kunlunRuntime = make_ref<KUNLUNRuntimeObj>(deviceID);
kunlunRuntime->initComm(taskName, WORLD_SIZE, deviceID);
// Create Graph and insert allReduce operation
Graph g = make_ref<GraphObj>(kunlunRuntime);
auto input =
g->addTensor(Shape{static_cast<int>(data.size())}, DataType::Float32);
auto op = g->addOp<AllGatherObj>(input, std::nullopt, WORLD_SIZE);
// Copy data from CPU to GPU
g->dataMalloc();
input->copyin(data);
// Run operation
kunlunRuntime->run(g);
// Copy output from GPU to CPU
for (int i = 0; i < WORLD_SIZE; ++i) {
auto result = op->getOutputs()[i]->clone(cpuRuntime);
EXPECT_TRUE(result->equalData(ans[i]));
}
}
TEST(KUNLUN_AllGather, run) {
vector<float> data[2] = {{2., 3.}, {5., 6.}};
vector<vector<float>> ans = {{2., 3.}, {5., 6.}};
std::vector<std::thread> threads;
for (int gpu = 0; gpu < WORLD_SIZE; ++gpu) {
threads.emplace_back(allGather, "test_all_gather", gpu, data[gpu], ans);
}
for (auto &thread : threads) {
thread.join();
}
}
} // namespace infini
#endif