mirror of
https://github.com/NVIDIA/cuda-samples.git
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189 lines
6.5 KiB
Plaintext
189 lines
6.5 KiB
Plaintext
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#define THREAD_N 256
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#define N 1024
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#define DIV_UP(a, b) (((a) + (b) - 1) / (b))
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// Includes, system
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#include <stdio.h>
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#include <helper_cuda.h>
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#include <helper_string.h>
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#include <helper_math.h>
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#include "cppOverload_kernel.cuh"
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const char *sampleName = "C++ Function Overloading";
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#define OUTPUT_ATTR(attr) \
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printf("Shared Size: %d\n", (int)attr.sharedSizeBytes); \
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printf("Constant Size: %d\n", (int)attr.constSizeBytes); \
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printf("Local Size: %d\n", (int)attr.localSizeBytes); \
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printf("Max Threads Per Block: %d\n", attr.maxThreadsPerBlock); \
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printf("Number of Registers: %d\n", attr.numRegs); \
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printf("PTX Version: %d\n", attr.ptxVersion); \
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printf("Binary Version: %d\n", attr.binaryVersion);
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bool check_func1(int *hInput, int *hOutput, int a) {
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for (int i = 0; i < N; ++i) {
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int cpuRes = hInput[i] * a + i;
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if (hOutput[i] != cpuRes) {
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return false;
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}
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}
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return true;
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}
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bool check_func2(int2 *hInput, int *hOutput, int a) {
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for (int i = 0; i < N; i++) {
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int cpuRes = (hInput[i].x + hInput[i].y) * a + i;
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if (hOutput[i] != cpuRes) {
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return false;
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}
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}
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return true;
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}
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bool check_func3(int *hInput1, int *hInput2, int *hOutput, int a) {
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for (int i = 0; i < N; i++) {
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if (hOutput[i] != (hInput1[i] + hInput2[i]) * a + i) {
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return false;
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}
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}
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return true;
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}
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int main(int argc, const char *argv[]) {
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int *hInput = NULL;
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int *hOutput = NULL;
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int *dInput = NULL;
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int *dOutput = NULL;
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printf("%s starting...\n", sampleName);
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int deviceCount;
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checkCudaErrors(cudaGetDeviceCount(&deviceCount));
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printf("Device Count: %d\n", deviceCount);
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int deviceID = findCudaDevice(argc, argv);
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cudaDeviceProp prop;
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checkCudaErrors(cudaGetDeviceProperties(&prop, deviceID));
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if (prop.major < 2) {
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printf(
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"ERROR: cppOverload requires GPU devices with compute SM 2.0 or "
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"higher.\n");
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printf("Current GPU device has compute SM%d.%d, Exiting...", prop.major,
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prop.minor);
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exit(EXIT_WAIVED);
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}
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checkCudaErrors(cudaSetDevice(deviceID));
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// Allocate device memory
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checkCudaErrors(cudaMalloc(&dInput, sizeof(int) * N * 2));
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checkCudaErrors(cudaMalloc(&dOutput, sizeof(int) * N));
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// Allocate host memory
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checkCudaErrors(cudaMallocHost(&hInput, sizeof(int) * N * 2));
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checkCudaErrors(cudaMallocHost(&hOutput, sizeof(int) * N));
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for (int i = 0; i < N * 2; i++) {
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hInput[i] = i;
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}
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// Copy data from host to device
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checkCudaErrors(
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cudaMemcpy(dInput, hInput, sizeof(int) * N * 2, cudaMemcpyHostToDevice));
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// Test C++ overloading
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bool testResult = true;
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bool funcResult = true;
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int a = 1;
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void (*func1)(const int *, int *, int);
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void (*func2)(const int2 *, int *, int);
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void (*func3)(const int *, const int *, int *, int);
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struct cudaFuncAttributes attr;
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// overload function 1
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func1 = simple_kernel;
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memset(&attr, 0, sizeof(attr));
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checkCudaErrors(cudaFuncSetCacheConfig(*func1, cudaFuncCachePreferShared));
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checkCudaErrors(cudaFuncGetAttributes(&attr, *func1));
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OUTPUT_ATTR(attr);
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(*func1)<<<DIV_UP(N, THREAD_N), THREAD_N>>>(dInput, dOutput, a);
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checkCudaErrors(
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cudaMemcpy(hOutput, dOutput, sizeof(int) * N, cudaMemcpyDeviceToHost));
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funcResult = check_func1(hInput, hOutput, a);
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printf("simple_kernel(const int *pIn, int *pOut, int a) %s\n\n",
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funcResult ? "PASSED" : "FAILED");
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testResult &= funcResult;
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// overload function 2
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func2 = simple_kernel;
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memset(&attr, 0, sizeof(attr));
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checkCudaErrors(cudaFuncSetCacheConfig(*func2, cudaFuncCachePreferShared));
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checkCudaErrors(cudaFuncGetAttributes(&attr, *func2));
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OUTPUT_ATTR(attr);
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(*func2)<<<DIV_UP(N, THREAD_N), THREAD_N>>>((int2 *)dInput, dOutput, a);
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checkCudaErrors(
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cudaMemcpy(hOutput, dOutput, sizeof(int) * N, cudaMemcpyDeviceToHost));
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funcResult = check_func2(reinterpret_cast<int2 *>(hInput), hOutput, a);
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printf("simple_kernel(const int2 *pIn, int *pOut, int a) %s\n\n",
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funcResult ? "PASSED" : "FAILED");
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testResult &= funcResult;
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// overload function 3
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func3 = simple_kernel;
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memset(&attr, 0, sizeof(attr));
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checkCudaErrors(cudaFuncSetCacheConfig(*func3, cudaFuncCachePreferShared));
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checkCudaErrors(cudaFuncGetAttributes(&attr, *func3));
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OUTPUT_ATTR(attr);
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(*func3)<<<DIV_UP(N, THREAD_N), THREAD_N>>>(dInput, dInput + N, dOutput, a);
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checkCudaErrors(
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cudaMemcpy(hOutput, dOutput, sizeof(int) * N, cudaMemcpyDeviceToHost));
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funcResult = check_func3(&hInput[0], &hInput[N], hOutput, a);
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printf(
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"simple_kernel(const int *pIn1, const int *pIn2, int *pOut, int a) "
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"%s\n\n",
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funcResult ? "PASSED" : "FAILED");
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testResult &= funcResult;
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checkCudaErrors(cudaFree(dInput));
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checkCudaErrors(cudaFree(dOutput));
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checkCudaErrors(cudaFreeHost(hOutput));
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checkCudaErrors(cudaFreeHost(hInput));
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checkCudaErrors(cudaDeviceSynchronize());
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exit(testResult ? EXIT_SUCCESS : EXIT_FAILURE);
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}
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