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cppOverload.cu
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/* Copyright (c) 2021, 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.
*/
#define THREAD_N 256
#define N 1024
#define DIV_UP(a, b) (((a) + (b)-1) / (b))
// Includes, system
#include <stdio.h>
#include <helper_cuda.h>
#include <helper_string.h>
#include <helper_math.h>
#include "cppOverload_kernel.cuh"
const char *sampleName = "C++ Function Overloading";
#define OUTPUT_ATTR(attr) \
printf("Shared Size: %d\n", (int)attr.sharedSizeBytes); \
printf("Constant Size: %d\n", (int)attr.constSizeBytes); \
printf("Local Size: %d\n", (int)attr.localSizeBytes); \
printf("Max Threads Per Block: %d\n", attr.maxThreadsPerBlock); \
printf("Number of Registers: %d\n", attr.numRegs); \
printf("PTX Version: %d\n", attr.ptxVersion); \
printf("Binary Version: %d\n", attr.binaryVersion);
bool check_func1(int *hInput, int *hOutput, int a) {
for (int i = 0; i < N; ++i) {
int cpuRes = hInput[i] * a + i;
if (hOutput[i] != cpuRes) {
return false;
}
}
return true;
}
bool check_func2(int2 *hInput, int *hOutput, int a) {
for (int i = 0; i < N; i++) {
int cpuRes = (hInput[i].x + hInput[i].y) * a + i;
if (hOutput[i] != cpuRes) {
return false;
}
}
return true;
}
bool check_func3(int *hInput1, int *hInput2, int *hOutput, int a) {
for (int i = 0; i < N; i++) {
if (hOutput[i] != (hInput1[i] + hInput2[i]) * a + i) {
return false;
}
}
return true;
}
int main(int argc, const char *argv[]) {
int *hInput = NULL;
int *hOutput = NULL;
int *dInput = NULL;
int *dOutput = NULL;
printf("%s starting...\n", sampleName);
int deviceCount;
checkCudaErrors(cudaGetDeviceCount(&deviceCount));
printf("Device Count: %d\n", deviceCount);
int deviceID = findCudaDevice(argc, argv);
cudaDeviceProp prop;
checkCudaErrors(cudaGetDeviceProperties(&prop, deviceID));
if (prop.major < 2) {
printf(
"ERROR: cppOverload requires GPU devices with compute SM 2.0 or "
"higher.\n");
printf("Current GPU device has compute SM%d.%d, Exiting...", prop.major,
prop.minor);
exit(EXIT_WAIVED);
}
checkCudaErrors(cudaSetDevice(deviceID));
// Allocate device memory
checkCudaErrors(cudaMalloc(&dInput, sizeof(int) * N * 2));
checkCudaErrors(cudaMalloc(&dOutput, sizeof(int) * N));
// Allocate host memory
checkCudaErrors(cudaMallocHost(&hInput, sizeof(int) * N * 2));
checkCudaErrors(cudaMallocHost(&hOutput, sizeof(int) * N));
for (int i = 0; i < N * 2; i++) {
hInput[i] = i;
}
// Copy data from host to device
checkCudaErrors(
cudaMemcpy(dInput, hInput, sizeof(int) * N * 2, cudaMemcpyHostToDevice));
// Test C++ overloading
bool testResult = true;
bool funcResult = true;
int a = 1;
void (*func1)(const int *, int *, int);
void (*func2)(const int2 *, int *, int);
void (*func3)(const int *, const int *, int *, int);
struct cudaFuncAttributes attr;
// overload function 1
func1 = simple_kernel;
memset(&attr, 0, sizeof(attr));
checkCudaErrors(cudaFuncSetCacheConfig(*func1, cudaFuncCachePreferShared));
checkCudaErrors(cudaFuncGetAttributes(&attr, *func1));
OUTPUT_ATTR(attr);
(*func1)<<<DIV_UP(N, THREAD_N), THREAD_N>>>(dInput, dOutput, a);
checkCudaErrors(
cudaMemcpy(hOutput, dOutput, sizeof(int) * N, cudaMemcpyDeviceToHost));
funcResult = check_func1(hInput, hOutput, a);
printf("simple_kernel(const int *pIn, int *pOut, int a) %s\n\n",
funcResult ? "PASSED" : "FAILED");
testResult &= funcResult;
// overload function 2
func2 = simple_kernel;
memset(&attr, 0, sizeof(attr));
checkCudaErrors(cudaFuncSetCacheConfig(*func2, cudaFuncCachePreferShared));
checkCudaErrors(cudaFuncGetAttributes(&attr, *func2));
OUTPUT_ATTR(attr);
(*func2)<<<DIV_UP(N, THREAD_N), THREAD_N>>>((int2 *)dInput, dOutput, a);
checkCudaErrors(
cudaMemcpy(hOutput, dOutput, sizeof(int) * N, cudaMemcpyDeviceToHost));
funcResult = check_func2(reinterpret_cast<int2 *>(hInput), hOutput, a);
printf("simple_kernel(const int2 *pIn, int *pOut, int a) %s\n\n",
funcResult ? "PASSED" : "FAILED");
testResult &= funcResult;
// overload function 3
func3 = simple_kernel;
memset(&attr, 0, sizeof(attr));
checkCudaErrors(cudaFuncSetCacheConfig(*func3, cudaFuncCachePreferShared));
checkCudaErrors(cudaFuncGetAttributes(&attr, *func3));
OUTPUT_ATTR(attr);
(*func3)<<<DIV_UP(N, THREAD_N), THREAD_N>>>(dInput, dInput + N, dOutput, a);
checkCudaErrors(
cudaMemcpy(hOutput, dOutput, sizeof(int) * N, cudaMemcpyDeviceToHost));
funcResult = check_func3(&hInput[0], &hInput[N], hOutput, a);
printf(
"simple_kernel(const int *pIn1, const int *pIn2, int *pOut, int a) "
"%s\n\n",
funcResult ? "PASSED" : "FAILED");
testResult &= funcResult;
checkCudaErrors(cudaFree(dInput));
checkCudaErrors(cudaFree(dOutput));
checkCudaErrors(cudaFreeHost(hOutput));
checkCudaErrors(cudaFreeHost(hInput));
checkCudaErrors(cudaDeviceSynchronize());
exit(testResult ? EXIT_SUCCESS : EXIT_FAILURE);
}