mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2024-11-25 13:29:17 +08:00
141 lines
5.5 KiB
Plaintext
141 lines
5.5 KiB
Plaintext
/* 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.
|
|
*/
|
|
|
|
//
|
|
// DESCRIPTION: Simple CUDA consumer rendering sample app
|
|
//
|
|
|
|
#include <EGL/egl.h>
|
|
#include <EGL/eglext.h>
|
|
#include <cuda.h>
|
|
#include <cuda_runtime.h>
|
|
#include <stdio.h>
|
|
#include <string.h>
|
|
|
|
#include "eglstrm_common.h"
|
|
|
|
extern bool isCrossDevice;
|
|
|
|
__device__ static unsigned int numErrors = 0, errorFound = 0;
|
|
__device__ void checkProducerDataGPU(char *data, int size, char expectedVal,
|
|
int frameNumber) {
|
|
if ((data[blockDim.x * blockIdx.x + threadIdx.x] != expectedVal) &&
|
|
(!errorFound)) {
|
|
printf("Producer FOUND:%d expected: %d at %d for trial %d %d\n",
|
|
data[blockDim.x * blockIdx.x + threadIdx.x], expectedVal,
|
|
(blockDim.x * blockIdx.x + threadIdx.x), frameNumber, numErrors);
|
|
numErrors++;
|
|
errorFound = 1;
|
|
return;
|
|
}
|
|
}
|
|
|
|
__device__ void checkConsumerDataGPU(char *data, int size, char expectedVal,
|
|
int frameNumber) {
|
|
if ((data[blockDim.x * blockIdx.x + threadIdx.x] != expectedVal) &&
|
|
(!errorFound)) {
|
|
printf("Consumer FOUND:%d expected: %d at %d for trial %d %d\n",
|
|
data[blockDim.x * blockIdx.x + threadIdx.x], expectedVal,
|
|
(blockDim.x * blockIdx.x + threadIdx.x), frameNumber, numErrors);
|
|
numErrors++;
|
|
errorFound = 1;
|
|
return;
|
|
}
|
|
}
|
|
|
|
__global__ void writeDataToBuffer(char *pSrc, char newVal) {
|
|
pSrc[blockDim.x * blockIdx.x + threadIdx.x] = newVal;
|
|
}
|
|
|
|
__global__ void testKernelConsumer(char *pSrc, char size, char expectedVal,
|
|
char newVal, int frameNumber) {
|
|
checkConsumerDataGPU(pSrc, size, expectedVal, frameNumber);
|
|
}
|
|
|
|
__global__ void testKernelProducer(char *pSrc, char size, char expectedVal,
|
|
char newVal, int frameNumber) {
|
|
checkProducerDataGPU(pSrc, size, expectedVal, frameNumber);
|
|
}
|
|
__global__ void getNumErrors(int *numErr) { *numErr = numErrors; }
|
|
|
|
cudaError_t cudaProducer_filter(cudaStream_t pStream, char *pSrc, int width,
|
|
int height, char expectedVal, char newVal,
|
|
int frameNumber) {
|
|
// in case where consumer is on dgpu and producer is on igpu when return is
|
|
// called the frame is not copied back to igpu. So the consumer changes is not
|
|
// visible to producer
|
|
if (isCrossDevice == 0) {
|
|
testKernelProducer<<<(width * height) / 1024, 1024, 1, pStream>>>(
|
|
pSrc, width * height, expectedVal, newVal, frameNumber);
|
|
}
|
|
writeDataToBuffer<<<(width * height) / 1024, 1024, 1, pStream>>>(pSrc,
|
|
newVal);
|
|
return cudaSuccess;
|
|
};
|
|
|
|
cudaError_t cudaConsumer_filter(cudaStream_t cStream, char *pSrc, int width,
|
|
int height, char expectedVal, char newVal,
|
|
int frameNumber) {
|
|
testKernelConsumer<<<(width * height) / 1024, 1024, 1, cStream>>>(
|
|
pSrc, width * height, expectedVal, newVal, frameNumber);
|
|
writeDataToBuffer<<<(width * height) / 1024, 1024, 1, cStream>>>(pSrc,
|
|
newVal);
|
|
return cudaSuccess;
|
|
};
|
|
|
|
cudaError_t cudaGetValueMismatch() {
|
|
int numErr_h;
|
|
int *numErr_d = NULL;
|
|
cudaError_t err = cudaSuccess;
|
|
err = cudaMalloc(&numErr_d, sizeof(int));
|
|
if (err != cudaSuccess) {
|
|
printf("Cuda Main: cudaMalloc failed with %s\n", cudaGetErrorString(err));
|
|
return err;
|
|
}
|
|
getNumErrors<<<1, 1>>>(numErr_d);
|
|
err = cudaDeviceSynchronize();
|
|
if (err != cudaSuccess) {
|
|
printf("Cuda Main: cudaDeviceSynchronize failed with %s\n",
|
|
cudaGetErrorString(err));
|
|
}
|
|
err = cudaMemcpy(&numErr_h, numErr_d, sizeof(int), cudaMemcpyDeviceToHost);
|
|
if (err != cudaSuccess) {
|
|
printf("Cuda Main: cudaMemcpy failed with %s\n", cudaGetErrorString(err));
|
|
cudaFree(numErr_d);
|
|
return err;
|
|
}
|
|
err = cudaFree(numErr_d);
|
|
if (err != cudaSuccess) {
|
|
printf("Cuda Main: cudaFree failed with %s\n", cudaGetErrorString(err));
|
|
return err;
|
|
}
|
|
if (numErr_h > 0) {
|
|
return cudaErrorUnknown;
|
|
}
|
|
return cudaSuccess;
|
|
}
|