13436a7e1f
Change-Id: I59d2e15b297b6ca2d5eee1a6dee642bdb01a3839
[ROCm/hip commit: d10124e1d7]
165 γραμμές
5.7 KiB
C++
165 γραμμές
5.7 KiB
C++
/*
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Copyright (c) 2015-2016 Advanced Micro Devices, Inc. All rights reserved.
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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*/
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/* HIT_START
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* BUILD: %t %s ../../test_common.cpp EXCLUDE_HIP_PLATFORM nvidia
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* TEST: %t
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* HIT_END
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*/
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#include <iostream>
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#include <vector>
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#include <chrono>
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#include "test_common.h"
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using namespace std;
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__global__ void vector_square(float *C_d, float *A_d, size_t N) {
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size_t idx = (blockIdx.x * blockDim.x + threadIdx.x);
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size_t stride = blockDim.x * gridDim.x ;
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for (size_t i = idx; i < N; i += stride) {
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C_d[i] = A_d[i] * A_d[i];
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}
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}
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int main(int argc, char* argv[]) {
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constexpr uint32_t numPartition = 4;
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float *dA[numPartition], *dC[numPartition];
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float *hA, *hC;
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size_t N = 25 * 1024 * 1024;
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size_t Nbytes = N * sizeof(float);
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vector<hipStream_t> streams(numPartition);
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vector<vector<uint32_t>> cuMasks(numPartition);
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stringstream ss[numPartition];
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int nGpu = 0;
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HIPCHECK(hipGetDeviceCount(&nGpu));
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if (nGpu < 1) {
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cout << "info: didn't find any GPU! skipping the test!\n";
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passed();
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return 0;
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}
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static int device = 0;
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HIPCHECK(hipSetDevice(device));
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hipDeviceProp_t props;
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HIPCHECK(hipGetDeviceProperties(&props, device));
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cout << "info: running on bus " << "0x" << props.pciBusID << " " << props.name <<
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" with " << props.multiProcessorCount << " CUs" << endl;
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hA = new float[Nbytes];
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HIPCHECK(hA == 0 ? hipErrorOutOfMemory : hipSuccess);
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hC = new float[Nbytes];
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HIPCHECK(hC == 0 ? hipErrorOutOfMemory : hipSuccess);
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for (size_t i = 0; i < N; i++) {
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hA[i] = 1.618f + i;
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}
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for (int np = 0; np < numPartition; np++) {
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HIPCHECK(hipMalloc(&dA[np], Nbytes));
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HIPCHECK(hipMalloc(&dC[np], Nbytes));
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// make unique CU masks in the multiple of dwords for each stream
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uint32_t temp = 0;
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uint32_t bit_index = np;
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for (int i = np; i < props.multiProcessorCount; i = i + 4) {
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temp |= 1UL << bit_index;
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if (bit_index >= 32) {
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cuMasks[np].push_back(temp);
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temp = 0;
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bit_index = np;
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temp |= 1UL << bit_index;
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}
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bit_index += 4;
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}
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if (bit_index != 0) {
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cuMasks[np].push_back(temp);
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}
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HIPCHECK(hipExtStreamCreateWithCUMask(&streams[np], cuMasks[np].size(), cuMasks[np].data()));
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HIPCHECK(hipMemcpy(dA[np], hA, Nbytes, hipMemcpyHostToDevice));
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ss[np] << std::hex;
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for (int i = cuMasks[np].size() - 1; i >= 0; i--) {
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ss[np] << cuMasks[np][i];
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}
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}
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const unsigned blocks = 512;
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const unsigned threadsPerBlock = 256;
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auto single_start = chrono::steady_clock::now();
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cout << "info: launch 'vector_square' kernel on one stream " << streams[0] << " with CU mask: 0x" << ss[0].str().c_str() << endl;
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hipLaunchKernelGGL(vector_square, dim3(blocks), dim3(threadsPerBlock), 0, streams[0], dC[0], dA[0], N);
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hipDeviceSynchronize();
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auto single_end = chrono::steady_clock::now();
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chrono::duration<double> single_kernel_time = single_end - single_start;
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HIPCHECK(hipMemcpy(hC, dC[0], Nbytes, hipMemcpyDeviceToHost));
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for (size_t i = 0; i < N; i++) {
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if (hC[i] != hA[i] * hA[i]) {
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cout << "info: validation failed for kernel launched at stream" << streams[0] << endl;
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HIPCHECK(hipErrorUnknown);
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}
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}
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cout << "info: launch 'vector_square' kernel on " << numPartition << " streams:" << endl;
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auto all_start = chrono::steady_clock::now();
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for (int np = 0; np < numPartition; np++) {
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cout << "info: launch 'vector_square' kernel on the stream " << streams[np] << " with CU mask: 0x" << ss[np].str().c_str() << endl;
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hipLaunchKernelGGL(vector_square, dim3(blocks), dim3(threadsPerBlock), 0,
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streams[np], dC[np], dA[np], N);
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}
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hipDeviceSynchronize();
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auto all_end = chrono::steady_clock::now();
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chrono::duration<double> all_kernel_time = all_end - all_start;
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for (int np = 0; np < numPartition; np++) {
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HIPCHECK(hipMemcpy(hC, dC[np], Nbytes, hipMemcpyDeviceToHost));
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for (size_t i = 0; i < N; i++) {
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if (hC[i] != hA[i] * hA[i]) {
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cout << "info: validation failed for kernel launched at stream" << streams[np] << endl;
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HIPCHECK(hipErrorUnknown);
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}
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}
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}
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cout << "info: kernel launched on one stream took: " << single_kernel_time.count() << " seconds" << endl;
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cout << "info: kernels launched on " << numPartition << " streams took: " << all_kernel_time.count() << " seconds" << endl;
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cout << "info: launching kernels on " << numPartition << " streams asynchronously is " << single_kernel_time.count() / (all_kernel_time.count() / numPartition)
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<< " times faster per stream than launching on one stream alone" << endl;
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delete [] hA;
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delete [] hC;
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for (int np = 0; np < numPartition; np++) {
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hipFree(dC[np]);
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hipFree(dA[np]);
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HIPCHECK(hipStreamDestroy(streams[np]));
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}
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passed();
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}
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