mirror of
https://github.com/NVIDIA/cuda-samples.git
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215 lines
7.9 KiB
Plaintext
215 lines
7.9 KiB
Plaintext
/* 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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// includes, system
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#include <stdlib.h>
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#include <stdio.h>
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#include <string.h>
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#include <math.h>
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// includes CUDA
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#include <cuda_runtime.h>
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// includes, project
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#include <helper_cuda.h>
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#include <helper_functions.h> // helper functions for SDK examples
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////////////////////////////////////////////////////////////////////////////////
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// declaration, forward
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void runTest(int argc, char **argv);
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cudaAccessPolicyWindow initAccessPolicyWindow(void) {
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cudaAccessPolicyWindow accessPolicyWindow = {0};
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accessPolicyWindow.base_ptr = (void *)0;
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accessPolicyWindow.num_bytes = 0;
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accessPolicyWindow.hitRatio = 0.f;
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accessPolicyWindow.hitProp = cudaAccessPropertyNormal;
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accessPolicyWindow.missProp = cudaAccessPropertyStreaming;
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return accessPolicyWindow;
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}
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////////////////////////////////////////////////////////////////////////////////
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//! Simple test kernel for device functionality
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//! @param data input data in global memory
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//! @param dataSize input data size
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//! @param bigData input bigData in global memory
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//! @param bigDataSize input bigData size
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//! @param hitcount how many data access are done within block
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////////////////////////////////////////////////////////////////////////////////
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static __global__ void kernCacheSegmentTest(int *data, int dataSize, int *trash,
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int bigDataSize, int hitCount) {
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__shared__ unsigned int hit;
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int row = blockIdx.y * blockDim.y + threadIdx.y;
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int col = blockIdx.x * blockDim.x + threadIdx.x;
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int tID = row * blockDim.y + col;
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uint32_t psRand = tID;
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atomicExch(&hit, 0);
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__syncthreads();
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while (hit < hitCount) {
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psRand ^= psRand << 13;
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psRand ^= psRand >> 17;
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psRand ^= psRand << 5;
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int idx = tID - psRand;
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if (idx < 0) {
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idx = -idx;
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}
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if ((tID % 2) == 0) {
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data[psRand % dataSize] = data[psRand % dataSize] + data[idx % dataSize];
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} else {
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trash[psRand % bigDataSize] =
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trash[psRand % bigDataSize] + trash[idx % bigDataSize];
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}
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atomicAdd(&hit, 1);
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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// Program main
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////////////////////////////////////////////////////////////////////////////////
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int main(int argc, char **argv) { runTest(argc, argv); }
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////////////////////////////////////////////////////////////////////////////////
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//! Run a simple test for CUDA
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////////////////////////////////////////////////////////////////////////////////
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void runTest(int argc, char **argv) {
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bool bTestResult = true;
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cudaAccessPolicyWindow accessPolicyWindow;
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cudaDeviceProp deviceProp;
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cudaStreamAttrValue streamAttrValue;
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cudaStream_t stream;
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cudaStreamAttrID streamAttrID;
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dim3 threads(32, 32);
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int *dataDevicePointer;
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int *dataHostPointer;
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int dataSize;
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int *bigDataDevicePointer;
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int *bigDataHostPointer;
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int bigDataSize;
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StopWatchInterface *timer = 0;
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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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int devID = findCudaDevice(argc, (const char **)argv);
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sdkCreateTimer(&timer);
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sdkStartTimer(&timer);
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// Get device properties
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checkCudaErrors(cudaGetDeviceProperties(&deviceProp, devID));
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dim3 blocks(deviceProp.maxGridSize[1], 1);
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// Make sure device the l2 optimization
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if (deviceProp.persistingL2CacheMaxSize == 0) {
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printf(
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"Waiving execution as device %d does not support persisting L2 "
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"Caching\n",
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devID);
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exit(EXIT_WAIVED);
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}
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// Create stream to assiocate with window
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checkCudaErrors(cudaStreamCreate(&stream));
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// Set the amount of l2 cache that will be persisting to maximum the device
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// can support
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checkCudaErrors(cudaDeviceSetLimit(cudaLimitPersistingL2CacheSize,
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deviceProp.persistingL2CacheMaxSize));
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// Stream attribute to set
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streamAttrID = cudaStreamAttributeAccessPolicyWindow;
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// Default window
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streamAttrValue.accessPolicyWindow = initAccessPolicyWindow();
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accessPolicyWindow = initAccessPolicyWindow();
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// Allocate size of both buffers
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bigDataSize = (deviceProp.l2CacheSize * 4) / sizeof(int);
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dataSize = (deviceProp.l2CacheSize / 4) / sizeof(int);
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// Allocate data
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checkCudaErrors(cudaMallocHost(&dataHostPointer, dataSize * sizeof(int)));
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checkCudaErrors(
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cudaMallocHost(&bigDataHostPointer, bigDataSize * sizeof(int)));
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for (int i = 0; i < bigDataSize; ++i) {
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if (i < dataSize) {
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dataHostPointer[i] = i;
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}
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bigDataHostPointer[bigDataSize - i - 1] = i;
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}
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checkCudaErrors(
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cudaMalloc((void **)&dataDevicePointer, dataSize * sizeof(int)));
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checkCudaErrors(
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cudaMalloc((void **)&bigDataDevicePointer, bigDataSize * sizeof(int)));
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checkCudaErrors(cudaMemcpyAsync(dataDevicePointer, dataHostPointer,
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dataSize * sizeof(int),
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cudaMemcpyHostToDevice, stream));
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checkCudaErrors(cudaMemcpyAsync(bigDataDevicePointer, bigDataHostPointer,
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bigDataSize * sizeof(int),
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cudaMemcpyHostToDevice, stream));
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// Make a window for the buffer of interest
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accessPolicyWindow.base_ptr = (void *)dataDevicePointer;
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accessPolicyWindow.num_bytes = dataSize * sizeof(int);
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accessPolicyWindow.hitRatio = 1.f;
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accessPolicyWindow.hitProp = cudaAccessPropertyPersisting;
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accessPolicyWindow.missProp = cudaAccessPropertyNormal;
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streamAttrValue.accessPolicyWindow = accessPolicyWindow;
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// Assign window to stream
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checkCudaErrors(
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cudaStreamSetAttribute(stream, streamAttrID, &streamAttrValue));
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// Demote any previous persisting lines
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checkCudaErrors(cudaCtxResetPersistingL2Cache());
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checkCudaErrors(cudaStreamSynchronize(stream));
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kernCacheSegmentTest<<<blocks, threads, 0, stream>>>(
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dataDevicePointer, dataSize, bigDataDevicePointer, bigDataSize, 0xAFFFF);
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checkCudaErrors(cudaStreamSynchronize(stream));
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// check if kernel execution generated and error
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getLastCudaError("Kernel execution failed");
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// Free memory
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checkCudaErrors(cudaFreeHost(dataHostPointer));
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checkCudaErrors(cudaFreeHost(bigDataHostPointer));
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checkCudaErrors(cudaFree(dataDevicePointer));
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checkCudaErrors(cudaFree(bigDataDevicePointer));
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sdkStopTimer(&timer);
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printf("Processing time: %f (ms)\n", sdkGetTimerValue(&timer));
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sdkDeleteTimer(&timer);
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exit(bTestResult ? EXIT_SUCCESS : EXIT_FAILURE);
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}
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