mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2024-11-29 04:39:16 +08:00
193 lines
6.7 KiB
C++
193 lines
6.7 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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#include <cuda_runtime.h>
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#include <helper_cuda.h>
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#include <helper_functions.h>
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#include "scan_common.h"
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int main(int argc, char **argv) {
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printf("%s Starting...\n\n", argv[0]);
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// Use command-line specified CUDA device, otherwise use device with highest
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// Gflops/s
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findCudaDevice(argc, (const char **)argv);
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uint *d_Input, *d_Output;
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uint *h_Input, *h_OutputCPU, *h_OutputGPU;
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StopWatchInterface *hTimer = NULL;
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const uint N = 13 * 1048576 / 2;
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printf("Allocating and initializing host arrays...\n");
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sdkCreateTimer(&hTimer);
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h_Input = (uint *)malloc(N * sizeof(uint));
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h_OutputCPU = (uint *)malloc(N * sizeof(uint));
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h_OutputGPU = (uint *)malloc(N * sizeof(uint));
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srand(2009);
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for (uint i = 0; i < N; i++) {
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h_Input[i] = rand();
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}
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printf("Allocating and initializing CUDA arrays...\n");
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checkCudaErrors(cudaMalloc((void **)&d_Input, N * sizeof(uint)));
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checkCudaErrors(cudaMalloc((void **)&d_Output, N * sizeof(uint)));
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checkCudaErrors(
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cudaMemcpy(d_Input, h_Input, N * sizeof(uint), cudaMemcpyHostToDevice));
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printf("Initializing CUDA-C scan...\n\n");
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initScan();
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int globalFlag = 1;
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size_t szWorkgroup;
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const int iCycles = 100;
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printf(
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"*** Running GPU scan for short arrays (%d identical iterations)...\n\n",
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iCycles);
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for (uint arrayLength = MIN_SHORT_ARRAY_SIZE;
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arrayLength <= MAX_SHORT_ARRAY_SIZE; arrayLength <<= 1) {
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printf("Running scan for %u elements (%u arrays)...\n", arrayLength,
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N / arrayLength);
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checkCudaErrors(cudaDeviceSynchronize());
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sdkResetTimer(&hTimer);
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sdkStartTimer(&hTimer);
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for (int i = 0; i < iCycles; i++) {
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szWorkgroup =
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scanExclusiveShort(d_Output, d_Input, N / arrayLength, arrayLength);
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}
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checkCudaErrors(cudaDeviceSynchronize());
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sdkStopTimer(&hTimer);
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double timerValue = 1.0e-3 * sdkGetTimerValue(&hTimer) / iCycles;
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printf("Validating the results...\n");
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printf("...reading back GPU results\n");
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checkCudaErrors(cudaMemcpy(h_OutputGPU, d_Output, N * sizeof(uint),
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cudaMemcpyDeviceToHost));
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printf(" ...scanExclusiveHost()\n");
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scanExclusiveHost(h_OutputCPU, h_Input, N / arrayLength, arrayLength);
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// Compare GPU results with CPU results and accumulate error for this test
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printf(" ...comparing the results\n");
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int localFlag = 1;
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for (uint i = 0; i < N; i++) {
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if (h_OutputCPU[i] != h_OutputGPU[i]) {
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localFlag = 0;
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break;
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}
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}
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// Log message on individual test result, then accumulate to global flag
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printf(" ...Results %s\n\n",
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(localFlag == 1) ? "Match" : "DON'T Match !!!");
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globalFlag = globalFlag && localFlag;
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// Data log
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if (arrayLength == MAX_SHORT_ARRAY_SIZE) {
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printf("\n");
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printf(
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"scan, Throughput = %.4f MElements/s, Time = %.5f s, Size = %u "
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"Elements, NumDevsUsed = %u, Workgroup = %u\n",
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(1.0e-6 * (double)arrayLength / timerValue), timerValue,
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(unsigned int)arrayLength, 1, (unsigned int)szWorkgroup);
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printf("\n");
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}
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}
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printf(
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"***Running GPU scan for large arrays (%u identical iterations)...\n\n",
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iCycles);
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for (uint arrayLength = MIN_LARGE_ARRAY_SIZE;
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arrayLength <= MAX_LARGE_ARRAY_SIZE; arrayLength <<= 1) {
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printf("Running scan for %u elements (%u arrays)...\n", arrayLength,
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N / arrayLength);
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checkCudaErrors(cudaDeviceSynchronize());
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sdkResetTimer(&hTimer);
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sdkStartTimer(&hTimer);
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for (int i = 0; i < iCycles; i++) {
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szWorkgroup =
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scanExclusiveLarge(d_Output, d_Input, N / arrayLength, arrayLength);
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}
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checkCudaErrors(cudaDeviceSynchronize());
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sdkStopTimer(&hTimer);
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double timerValue = 1.0e-3 * sdkGetTimerValue(&hTimer) / iCycles;
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printf("Validating the results...\n");
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printf("...reading back GPU results\n");
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checkCudaErrors(cudaMemcpy(h_OutputGPU, d_Output, N * sizeof(uint),
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cudaMemcpyDeviceToHost));
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printf("...scanExclusiveHost()\n");
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scanExclusiveHost(h_OutputCPU, h_Input, N / arrayLength, arrayLength);
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// Compare GPU results with CPU results and accumulate error for this test
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printf(" ...comparing the results\n");
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int localFlag = 1;
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for (uint i = 0; i < N; i++) {
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if (h_OutputCPU[i] != h_OutputGPU[i]) {
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localFlag = 0;
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break;
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}
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}
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// Log message on individual test result, then accumulate to global flag
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printf(" ...Results %s\n\n",
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(localFlag == 1) ? "Match" : "DON'T Match !!!");
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globalFlag = globalFlag && localFlag;
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// Data log
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if (arrayLength == MAX_LARGE_ARRAY_SIZE) {
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printf("\n");
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printf(
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"scan, Throughput = %.4f MElements/s, Time = %.5f s, Size = %u "
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"Elements, NumDevsUsed = %u, Workgroup = %u\n",
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(1.0e-6 * (double)arrayLength / timerValue), timerValue,
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(unsigned int)arrayLength, 1, (unsigned int)szWorkgroup);
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printf("\n");
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}
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}
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printf("Shutting down...\n");
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closeScan();
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checkCudaErrors(cudaFree(d_Output));
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checkCudaErrors(cudaFree(d_Input));
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sdkDeleteTimer(&hTimer);
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// pass or fail (cumulative... all tests in the loop)
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exit(globalFlag ? EXIT_SUCCESS : EXIT_FAILURE);
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}
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