Merge pull request #1101 from emankov/master
[HIPIFY][tests] Add reverse engineered HIP sample MatrixTranspose
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// RUN: %run_test hipify "%s" "%t" %hipify_args %clang_args
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/*
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Copyright (c) 2015-2019 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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#include <iostream>
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// CHECK: #include <hip/hip_runtime.h>
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#include <cuda.h>
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#define WIDTH 1024
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#define NUM (WIDTH * WIDTH)
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#define THREADS_PER_BLOCK_X 4
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#define THREADS_PER_BLOCK_Y 4
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#define THREADS_PER_BLOCK_Z 1
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// Device (Kernel) function, it must be void
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__global__ void matrixTranspose(float* out, float* in, const int width) {
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int x = blockDim.x * blockIdx.x + threadIdx.x;
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int y = blockDim.y * blockIdx.y + threadIdx.y;
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out[y * width + x] = in[x * width + y];
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}
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// CPU implementation of matrix transpose
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void matrixTransposeCPUReference(float* output, float* input, const unsigned int width) {
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for (unsigned int j = 0; j < width; j++) {
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for (unsigned int i = 0; i < width; i++) {
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output[i * width + j] = input[j * width + i];
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}
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}
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}
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int main() {
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float* Matrix;
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float* TransposeMatrix;
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float* cpuTransposeMatrix;
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float* gpuMatrix;
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float* gpuTransposeMatrix;
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// CHECK: hipDeviceProp_t devProp;
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cudaDeviceProp devProp;
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// CHECK: hipGetDeviceProperties(&devProp, 0);
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cudaGetDeviceProperties(&devProp, 0);
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std::cout << "Device name " << devProp.name << std::endl;
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int i;
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int errors;
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Matrix = (float*)malloc(NUM * sizeof(float));
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TransposeMatrix = (float*)malloc(NUM * sizeof(float));
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cpuTransposeMatrix = (float*)malloc(NUM * sizeof(float));
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// initialize the input data
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for (i = 0; i < NUM; i++) {
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Matrix[i] = (float)i * 10.0f;
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}
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// allocate the memory on the device side
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// CHECK: hipMalloc((void**)&gpuMatrix, NUM * sizeof(float));
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cudaMalloc((void**)&gpuMatrix, NUM * sizeof(float));
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// CHECK: hipMalloc((void**)&gpuTransposeMatrix, NUM * sizeof(float));
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cudaMalloc((void**)&gpuTransposeMatrix, NUM * sizeof(float));
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// Memory transfer from host to device
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// CHECK: hipMemcpy(gpuMatrix, Matrix, NUM * sizeof(float), hipMemcpyHostToDevice);
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cudaMemcpy(gpuMatrix, Matrix, NUM * sizeof(float), cudaMemcpyHostToDevice);
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// Lauching kernel from host
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dim3 dimGrid(WIDTH / THREADS_PER_BLOCK_X, WIDTH / THREADS_PER_BLOCK_Y);
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dim3 dimBlock(THREADS_PER_BLOCK_X, THREADS_PER_BLOCK_Y);
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// CHECK: hipLaunchKernelGGL(matrixTranspose, dim3(dimGrid), dim3(dimBlock), 0, 0, gpuTransposeMatrix, gpuMatrix, WIDTH);
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matrixTranspose <<<dimGrid, dimBlock>>>(gpuTransposeMatrix, gpuMatrix, WIDTH);
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// Memory transfer from device to host
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// CHECK: hipMemcpy(TransposeMatrix, gpuTransposeMatrix, NUM * sizeof(float), hipMemcpyDeviceToHost);
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cudaMemcpy(TransposeMatrix, gpuTransposeMatrix, NUM * sizeof(float), cudaMemcpyDeviceToHost);
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// CPU MatrixTranspose computation
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matrixTransposeCPUReference(cpuTransposeMatrix, Matrix, WIDTH);
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// verify the results
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errors = 0;
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double eps = 1.0E-6;
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for (i = 0; i < NUM; i++) {
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if (std::abs(TransposeMatrix[i] - cpuTransposeMatrix[i]) > eps) {
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errors++;
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}
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}
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if (errors != 0) {
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printf("FAILED: %d errors\n", errors);
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} else {
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printf("PASSED!\n");
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}
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// free the resources on device side
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// CHECK: hipFree(gpuMatrix);
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cudaFree(gpuMatrix);
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// CHECK: hipFree(gpuTransposeMatrix);
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cudaFree(gpuTransposeMatrix);
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// free the resources on host side
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free(Matrix);
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free(TransposeMatrix);
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free(cpuTransposeMatrix);
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return errors;
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}
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