mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2024-12-01 12:09:15 +08:00
101 lines
3.7 KiB
C++
101 lines
3.7 KiB
C++
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
|
|
*
|
|
* Redistribution and use in source and binary forms, with or without
|
|
* modification, are permitted provided that the following conditions
|
|
* are met:
|
|
* * Redistributions of source code must retain the above copyright
|
|
* notice, this list of conditions and the following disclaimer.
|
|
* * Redistributions in binary form must reproduce the above copyright
|
|
* notice, this list of conditions and the following disclaimer in the
|
|
* documentation and/or other materials provided with the distribution.
|
|
* * Neither the name of NVIDIA CORPORATION nor the names of its
|
|
* contributors may be used to endorse or promote products derived
|
|
* from this software without specific prior written permission.
|
|
*
|
|
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
|
|
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
|
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
|
|
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
|
|
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
|
|
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
|
|
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
|
|
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
|
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
*/
|
|
|
|
#include <cuda.h>
|
|
#include <vector>
|
|
#include "cudaNvSci.h"
|
|
#include <helper_cuda.h>
|
|
#include <helper_image.h>
|
|
|
|
void loadImageData(const std::string &filename, const char **argv,
|
|
unsigned char **image_data, uint32_t &imageWidth,
|
|
uint32_t &imageHeight) {
|
|
// load image (needed so we can get the width and height before we create
|
|
// the window
|
|
char *image_path = sdkFindFilePath(filename.c_str(), argv[0]);
|
|
|
|
if (image_path == 0) {
|
|
printf("Error finding image file '%s'\n", filename.c_str());
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
sdkLoadPPM4(image_path, image_data, &imageWidth, &imageHeight);
|
|
|
|
if (!image_data) {
|
|
printf("Error opening file '%s'\n", image_path);
|
|
exit(EXIT_FAILURE);
|
|
}
|
|
|
|
printf("Loaded '%s', %d x %d pixels\n", image_path, imageWidth, imageHeight);
|
|
}
|
|
|
|
int main(int argc, const char **argv) {
|
|
int numOfGPUs = 0;
|
|
std::vector<int> deviceIds;
|
|
checkCudaErrors(cudaGetDeviceCount(&numOfGPUs));
|
|
|
|
printf("%d GPUs found\n", numOfGPUs);
|
|
if (!numOfGPUs) {
|
|
exit(EXIT_WAIVED);
|
|
} else {
|
|
for (int devID = 0; devID < numOfGPUs; devID++) {
|
|
int major = 0, minor = 0;
|
|
checkCudaErrors(cudaDeviceGetAttribute(
|
|
&major, cudaDevAttrComputeCapabilityMajor, devID));
|
|
checkCudaErrors(cudaDeviceGetAttribute(
|
|
&minor, cudaDevAttrComputeCapabilityMinor, devID));
|
|
if (major >= 6) {
|
|
deviceIds.push_back(devID);
|
|
}
|
|
}
|
|
if (deviceIds.size() == 0) {
|
|
printf(
|
|
"cudaNvSci requires one or more GPUs of Pascal(SM 6.0) or higher "
|
|
"archs\nWaiving..\n");
|
|
exit(EXIT_WAIVED);
|
|
}
|
|
}
|
|
|
|
std::string image_filename = "teapot1024.ppm";
|
|
|
|
if (checkCmdLineFlag(argc, (const char **)argv, "file")) {
|
|
getCmdLineArgumentString(argc, (const char **)argv, "file",
|
|
(char **)&image_filename);
|
|
}
|
|
|
|
uint32_t imageWidth = 0;
|
|
uint32_t imageHeight = 0;
|
|
unsigned char *image_data = NULL;
|
|
|
|
loadImageData(image_filename, argv, &image_data, imageWidth, imageHeight);
|
|
|
|
cudaNvSci cudaNvSciApp(deviceIds.size() > 1, deviceIds, image_data,
|
|
imageWidth, imageHeight);
|
|
cudaNvSciApp.runCudaNvSci(image_filename);
|
|
|
|
return EXIT_SUCCESS;
|
|
} |