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/* 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.
*/
/* Template project which demonstrates the basics on how to setup a project
* example application.
* Host code.
*/
// includes, system
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
// includes CUDA
#include <cuda_runtime.h>
// includes, project
#include <helper_cuda.h>
#include <helper_functions.h> // helper functions for SDK examples
////////////////////////////////////////////////////////////////////////////////
// declaration, forward
void runTest(int argc, char **argv);
extern "C" void computeGold(float *reference, float *idata,
const unsigned int len);
////////////////////////////////////////////////////////////////////////////////
//! Simple test kernel for device functionality
//! @param g_idata input data in global memory
//! @param g_odata output data in global memory
////////////////////////////////////////////////////////////////////////////////
__global__ void testKernel(float *g_idata, float *g_odata) {
// shared memory
// the size is determined by the host application
extern __shared__ float sdata[];
// access thread id
const unsigned int tid = threadIdx.x;
// access number of threads in this block
const unsigned int num_threads = blockDim.x;
// read in input data from global memory
sdata[tid] = g_idata[tid];
__syncthreads();
// perform some computations
sdata[tid] = (float)num_threads * sdata[tid];
__syncthreads();
// write data to global memory
g_odata[tid] = sdata[tid];
}
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) { runTest(argc, argv); }
////////////////////////////////////////////////////////////////////////////////
//! Run a simple test for CUDA
////////////////////////////////////////////////////////////////////////////////
void runTest(int argc, char **argv) {
bool bTestResult = true;
printf("%s Starting...\n\n", argv[0]);
// use command-line specified CUDA device, otherwise use device with highest
// Gflops/s
int devID = findCudaDevice(argc, (const char **)argv);
StopWatchInterface *timer = 0;
sdkCreateTimer(&timer);
sdkStartTimer(&timer);
unsigned int num_threads = 32;
unsigned int mem_size = sizeof(float) * num_threads;
// allocate host memory
float *h_idata = (float *)malloc(mem_size);
// initalize the memory
for (unsigned int i = 0; i < num_threads; ++i) {
h_idata[i] = (float)i;
}
// allocate device memory
float *d_idata;
checkCudaErrors(cudaMalloc((void **)&d_idata, mem_size));
// copy host memory to device
checkCudaErrors(
cudaMemcpy(d_idata, h_idata, mem_size, cudaMemcpyHostToDevice));
// allocate device memory for result
float *d_odata;
checkCudaErrors(cudaMalloc((void **)&d_odata, mem_size));
// setup execution parameters
dim3 grid(1, 1, 1);
dim3 threads(num_threads, 1, 1);
// execute the kernel
testKernel<<<grid, threads, mem_size>>>(d_idata, d_odata);
// check if kernel execution generated and error
getLastCudaError("Kernel execution failed");
// allocate mem for the result on host side
float *h_odata = (float *)malloc(mem_size);
// copy result from device to host
checkCudaErrors(cudaMemcpy(h_odata, d_odata, sizeof(float) * num_threads,
cudaMemcpyDeviceToHost));
sdkStopTimer(&timer);
printf("Processing time: %f (ms)\n", sdkGetTimerValue(&timer));
sdkDeleteTimer(&timer);
// compute reference solution
float *reference = (float *)malloc(mem_size);
computeGold(reference, h_idata, num_threads);
// check result
if (checkCmdLineFlag(argc, (const char **)argv, "regression")) {
// write file for regression test
sdkWriteFile("./data/regression.dat", h_odata, num_threads, 0.0f, false);
} else {
// custom output handling when no regression test running
// in this case check if the result is equivalent to the expected solution
bTestResult = compareData(reference, h_odata, num_threads, 0.0f, 0.0f);
}
// cleanup memory
free(h_idata);
free(h_odata);
free(reference);
checkCudaErrors(cudaFree(d_idata));
checkCudaErrors(cudaFree(d_odata));
exit(bTestResult ? EXIT_SUCCESS : EXIT_FAILURE);
}
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