mirror of
https://github.com/NVIDIA/cuda-samples.git
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283 lines
9.6 KiB
Plaintext
283 lines
9.6 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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/* A CUDA program that demonstrates how to compute a stereo disparity map using
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* SIMD SAD (Sum of Absolute Difference) intrinsics
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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, kernels
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#include <cuda_runtime.h>
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#include "stereoDisparity_kernel.cuh"
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// includes, project
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#include <helper_functions.h> // helper for shared that are common to CUDA Samples
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#include <helper_cuda.h> // helper for checking cuda initialization and error checking
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#include <helper_string.h> // helper functions for string parsing
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static const char *sSDKsample = "[stereoDisparity]\0";
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int iDivUp(int a, int b) { return ((a % b) != 0) ? (a / b + 1) : (a / b); }
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////////////////////////////////////////////////////////////////////////////////
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// declaration, forward
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void runTest(int argc, char **argv);
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////////////////////////////////////////////////////////////////////////////////
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// Program main
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////////////////////////////////////////////////////////////////////////////////
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int main(int argc, char **argv) {
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printf("%s Starting...\n\n", sSDKsample);
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runTest(argc, argv);
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}
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////////////////////////////////////////////////////////////////////////////////
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//! CUDA Sample for calculating depth maps
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////////////////////////////////////////////////////////////////////////////////
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void runTest(int argc, char **argv) {
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cudaDeviceProp deviceProp;
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deviceProp.major = 0;
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deviceProp.minor = 0;
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int dev = 0;
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// This will pick the best possible CUDA capable device
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dev = findCudaDevice(argc, (const char **)argv);
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checkCudaErrors(cudaGetDeviceProperties(&deviceProp, dev));
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// Statistics about the GPU device
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printf(
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"> GPU device has %d Multi-Processors, SM %d.%d compute capabilities\n\n",
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deviceProp.multiProcessorCount, deviceProp.major, deviceProp.minor);
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StopWatchInterface *timer;
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sdkCreateTimer(&timer);
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// Search parameters
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int minDisp = -16;
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int maxDisp = 0;
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// Load image data
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// allocate mem for the images on host side
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// initialize pointers to NULL to request lib call to allocate as needed
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// PPM images are loaded into 4 byte/pixel memory (RGBX)
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unsigned char *h_img0 = NULL;
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unsigned char *h_img1 = NULL;
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unsigned int w, h;
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char *fname0 = sdkFindFilePath("stereo.im0.640x533.ppm", argv[0]);
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char *fname1 = sdkFindFilePath("stereo.im1.640x533.ppm", argv[0]);
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printf("Loaded <%s> as image 0\n", fname0);
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if (!sdkLoadPPM4ub(fname0, &h_img0, &w, &h)) {
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fprintf(stderr, "Failed to load <%s>\n", fname0);
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}
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printf("Loaded <%s> as image 1\n", fname1);
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if (!sdkLoadPPM4ub(fname1, &h_img1, &w, &h)) {
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fprintf(stderr, "Failed to load <%s>\n", fname1);
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}
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dim3 numThreads = dim3(blockSize_x, blockSize_y, 1);
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dim3 numBlocks = dim3(iDivUp(w, numThreads.x), iDivUp(h, numThreads.y));
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unsigned int numData = w * h;
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unsigned int memSize = sizeof(int) * numData;
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// allocate mem for the result on host side
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unsigned int *h_odata = (unsigned int *)malloc(memSize);
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// initialize the memory
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for (unsigned int i = 0; i < numData; i++) h_odata[i] = 0;
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// allocate device memory for result
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unsigned int *d_odata, *d_img0, *d_img1;
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checkCudaErrors(cudaMalloc((void **)&d_odata, memSize));
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checkCudaErrors(cudaMalloc((void **)&d_img0, memSize));
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checkCudaErrors(cudaMalloc((void **)&d_img1, memSize));
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// copy host memory to device to initialize to zeros
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checkCudaErrors(cudaMemcpy(d_img0, h_img0, memSize, cudaMemcpyHostToDevice));
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checkCudaErrors(cudaMemcpy(d_img1, h_img1, memSize, cudaMemcpyHostToDevice));
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checkCudaErrors(
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cudaMemcpy(d_odata, h_odata, memSize, cudaMemcpyHostToDevice));
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cudaChannelFormatDesc ca_desc0 = cudaCreateChannelDesc<unsigned int>();
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cudaChannelFormatDesc ca_desc1 = cudaCreateChannelDesc<unsigned int>();
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cudaTextureObject_t tex2Dleft, tex2Dright;
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cudaResourceDesc texRes;
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memset(&texRes, 0, sizeof(cudaResourceDesc));
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texRes.resType = cudaResourceTypePitch2D;
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texRes.res.pitch2D.devPtr = d_img0;
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texRes.res.pitch2D.desc = ca_desc0;
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texRes.res.pitch2D.width = w;
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texRes.res.pitch2D.height = h;
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texRes.res.pitch2D.pitchInBytes = w * 4;
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cudaTextureDesc texDescr;
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memset(&texDescr, 0, sizeof(cudaTextureDesc));
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texDescr.normalizedCoords = false;
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texDescr.filterMode = cudaFilterModePoint;
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texDescr.addressMode[0] = cudaAddressModeClamp;
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texDescr.addressMode[1] = cudaAddressModeClamp;
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texDescr.readMode = cudaReadModeElementType;
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checkCudaErrors(
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cudaCreateTextureObject(&tex2Dleft, &texRes, &texDescr, NULL));
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memset(&texRes, 0, sizeof(cudaResourceDesc));
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texRes.resType = cudaResourceTypePitch2D;
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texRes.res.pitch2D.devPtr = d_img1;
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texRes.res.pitch2D.desc = ca_desc1;
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texRes.res.pitch2D.width = w;
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texRes.res.pitch2D.height = h;
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texRes.res.pitch2D.pitchInBytes = w * 4;
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memset(&texDescr, 0, sizeof(cudaTextureDesc));
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texDescr.normalizedCoords = false;
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texDescr.filterMode = cudaFilterModePoint;
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texDescr.addressMode[0] = cudaAddressModeClamp;
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texDescr.addressMode[1] = cudaAddressModeClamp;
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texDescr.readMode = cudaReadModeElementType;
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checkCudaErrors(
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cudaCreateTextureObject(&tex2Dright, &texRes, &texDescr, NULL));
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// First run the warmup kernel (which we'll use to get the GPU in the correct
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// max power state
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stereoDisparityKernel<<<numBlocks, numThreads>>>(
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d_img0, d_img1, d_odata, w, h, minDisp, maxDisp, tex2Dleft, tex2Dright);
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cudaDeviceSynchronize();
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// Allocate CUDA events that we'll use for timing
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cudaEvent_t start, stop;
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checkCudaErrors(cudaEventCreate(&start));
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checkCudaErrors(cudaEventCreate(&stop));
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printf("Launching CUDA stereoDisparityKernel()\n");
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// Record the start event
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checkCudaErrors(cudaEventRecord(start, NULL));
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// launch the stereoDisparity kernel
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stereoDisparityKernel<<<numBlocks, numThreads>>>(
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d_img0, d_img1, d_odata, w, h, minDisp, maxDisp, tex2Dleft, tex2Dright);
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// Record the stop event
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checkCudaErrors(cudaEventRecord(stop, NULL));
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// Wait for the stop event to complete
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checkCudaErrors(cudaEventSynchronize(stop));
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// Check to make sure the kernel didn't fail
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getLastCudaError("Kernel execution failed");
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float msecTotal = 0.0f;
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checkCudaErrors(cudaEventElapsedTime(&msecTotal, start, stop));
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// Copy result from device to host for verification
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checkCudaErrors(
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cudaMemcpy(h_odata, d_odata, memSize, cudaMemcpyDeviceToHost));
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printf("Input Size [%dx%d], ", w, h);
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printf("Kernel size [%dx%d], ", (2 * RAD + 1), (2 * RAD + 1));
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printf("Disparities [%d:%d]\n", minDisp, maxDisp);
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printf("GPU processing time : %.4f (ms)\n", msecTotal);
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printf("Pixel throughput : %.3f Mpixels/sec\n",
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((float)(w * h * 1000.f) / msecTotal) / 1000000);
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// calculate sum of resultant GPU image
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unsigned int checkSum = 0;
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for (unsigned int i = 0; i < w * h; i++) {
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checkSum += h_odata[i];
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}
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printf("GPU Checksum = %u, ", checkSum);
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// write out the resulting disparity image.
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unsigned char *dispOut = (unsigned char *)malloc(numData);
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int mult = 20;
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const char *fnameOut = "output_GPU.pgm";
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for (unsigned int i = 0; i < numData; i++) {
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dispOut[i] = (int)h_odata[i] * mult;
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}
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printf("GPU image: <%s>\n", fnameOut);
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sdkSavePGM(fnameOut, dispOut, w, h);
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// compute reference solution
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printf("Computing CPU reference...\n");
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cpu_gold_stereo((unsigned int *)h_img0, (unsigned int *)h_img1,
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(unsigned int *)h_odata, w, h, minDisp, maxDisp);
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unsigned int cpuCheckSum = 0;
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for (unsigned int i = 0; i < w * h; i++) {
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cpuCheckSum += h_odata[i];
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}
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printf("CPU Checksum = %u, ", cpuCheckSum);
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const char *cpuFnameOut = "output_CPU.pgm";
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for (unsigned int i = 0; i < numData; i++) {
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dispOut[i] = (int)h_odata[i] * mult;
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}
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printf("CPU image: <%s>\n", cpuFnameOut);
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sdkSavePGM(cpuFnameOut, dispOut, w, h);
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// cleanup memory
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checkCudaErrors(cudaFree(d_odata));
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checkCudaErrors(cudaFree(d_img0));
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checkCudaErrors(cudaFree(d_img1));
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if (h_odata != NULL) free(h_odata);
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if (h_img0 != NULL) free(h_img0);
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if (h_img1 != NULL) free(h_img1);
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if (dispOut != NULL) free(dispOut);
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sdkDeleteTimer(&timer);
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exit((checkSum == cpuCheckSum) ? EXIT_SUCCESS : EXIT_FAILURE);
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}
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