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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.
*/
// System includes.
#include <stdio.h>
#include <iostream>
// STL.
#include <vector>
// CUDA runtime.
#include <cuda_runtime.h>
// Helper functions and utilities to work with CUDA.
#include <helper_functions.h>
#include <helper_cuda.h>
// Device library includes.
#include "simpleDeviceLibrary.cuh"
using std::cout;
using std::endl;
using std::vector;
#define EPS 1e-5
typedef unsigned int uint;
typedef float (*deviceFunc)(float);
const char *sampleName = "simpleSeparateCompilation";
////////////////////////////////////////////////////////////////////////////////
// Auto-Verification Code
bool testResult = true;
////////////////////////////////////////////////////////////////////////////////
// Static device pointers to __device__ functions.
__device__ deviceFunc dMultiplyByTwoPtr = multiplyByTwo;
__device__ deviceFunc dDivideByTwoPtr = divideByTwo;
////////////////////////////////////////////////////////////////////////////////
// Kernels
////////////////////////////////////////////////////////////////////////////////
//! Transforms vector.
//! Applies the __device__ function "f" to each element of the vector "v".
////////////////////////////////////////////////////////////////////////////////
__global__ void transformVector(float *v, deviceFunc f, uint size) {
uint tid = blockIdx.x * blockDim.x + threadIdx.x;
if (tid < size) {
v[tid] = (*f)(v[tid]);
}
}
////////////////////////////////////////////////////////////////////////////////
// Declaration, forward
void runTest(int argc, const char **argv);
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) {
cout << sampleName << " starting..." << endl;
runTest(argc, (const char **)argv);
cout << sampleName << " completed, returned " << (testResult ? "OK" : "ERROR")
<< endl;
exit(testResult ? EXIT_SUCCESS : EXIT_FAILURE);
}
void runTest(int argc, const char **argv) {
try {
// This will pick the best possible CUDA capable device.
findCudaDevice(argc, (const char **)argv);
// Create host vector.
const uint kVectorSize = 1000;
vector<float> hVector(kVectorSize);
for (uint i = 0; i < kVectorSize; ++i) {
hVector[i] = rand() / static_cast<float>(RAND_MAX);
}
// Create and populate device vector.
float *dVector;
checkCudaErrors(cudaMalloc(&dVector, kVectorSize * sizeof(float)));
checkCudaErrors(cudaMemcpy(dVector, &hVector[0],
kVectorSize * sizeof(float),
cudaMemcpyHostToDevice));
// Kernel configuration, where a one-dimensional
// grid and one-dimensional blocks are configured.
const int nThreads = 1024;
const int nBlocks = 1;
dim3 dimGrid(nBlocks);
dim3 dimBlock(nThreads);
// Test library functions.
deviceFunc hFunctionPtr;
cudaMemcpyFromSymbol(&hFunctionPtr, dMultiplyByTwoPtr, sizeof(deviceFunc));
transformVector<<<dimGrid, dimBlock>>>(dVector, hFunctionPtr, kVectorSize);
checkCudaErrors(cudaGetLastError());
cudaMemcpyFromSymbol(&hFunctionPtr, dDivideByTwoPtr, sizeof(deviceFunc));
transformVector<<<dimGrid, dimBlock>>>(dVector, hFunctionPtr, kVectorSize);
checkCudaErrors(cudaGetLastError());
// Download results.
vector<float> hResultVector(kVectorSize);
checkCudaErrors(cudaMemcpy(&hResultVector[0], dVector,
kVectorSize * sizeof(float),
cudaMemcpyDeviceToHost));
// Check results.
for (int i = 0; i < kVectorSize; ++i) {
if (fabs(hVector[i] - hResultVector[i]) > EPS) {
cout << "Computations were incorrect..." << endl;
testResult = false;
break;
}
}
// Free resources.
if (dVector) checkCudaErrors(cudaFree(dVector));
} catch (...) {
cout << "Error occured, exiting..." << endl;
exit(EXIT_FAILURE);
}
}
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