CUDA —— 1.1、C++与CUDA混合编程，C++调用cuda自定义类进行运算操作（附：Windows下Vs2017编程环境配置）

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于 2025-06-26 15:13:55 发布

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分类专栏： CUDA 文章标签： C++ Windows CUDA Vs2017

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本文链接：https://blog.youkuaiyun.com/automoblie0/article/details/148924919

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运行效果

由于cuda进行运算是非常快的。本文介绍通过C++调用自定义的cuda类接口，将耗时运算操作交由cuda进行计算。

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正问

1、打开vs2017，创建C++空项目，并创建main.cpp写入部分代码

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2、创建cuda文件与头文件

(1)、右键项目名称 - 添加 - 新建项 - Visual C++，分两次分别创建"CUDA 11.4 C/C++ File"与"CUDA 11.4 C/C++ Header"

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(2)、将如下代码分别写入3个代码文件

main.cpp

#include <iostream>

#include "main.cuh"

int main()
{
	CudaTest TEST;
	TEST.RunCalc();

	system("pause");
	return 0;
}

CudaTest.cuh

#ifndef MAIN_CUH
#define MAIN_CUH

#include "cuda_runtime.h"
#include "device_launch_parameters.h"

#include <stdio.h>

class CudaTest
{
public:
	CudaTest();

	int RunCalc();
};

#endif

CudaTest.cu


#include "main.cuh"

#include <Windows.h>

CudaTest::CudaTest()
{

}


cudaError_t addWithCuda(int *c, const int *a, const int *b, unsigned int size);

__global__ void addKernel(int *c, const int *a, const int *b)
{
	int i = threadIdx.x;
	c[i] = a[i] + b[i];
}

int CudaTest::RunCalc()
{
	const int arraySize = 5;
	const int a[arraySize] = { 1, 2, 3, 4, 5 };
	const int b[arraySize] = { 10, 20, 30, 40, 50 };
	int c[arraySize] = { 0 };

	cudaError_t cudaStatus = cudaSuccess;
	for (unsigned short index = 0; index < 3000; ++index)
	{
		// Add vectors in parallel.
		cudaStatus = addWithCuda(c, a, b, arraySize);
		if (cudaStatus != cudaSuccess) { fprintf(stderr, "addWithCuda failed!"); return 1; }

		printf("%d --- {1,2,3,4,5} + {10,20,30,40,50} = {%d,%d,%d,%d,%d}\n", index,c[0], c[1], c[2], c[3], c[4]);

		Sleep(1);
	}

	// cudaDeviceReset must be called before exiting in order for profiling and
	// tracing tools such as Nsight and Visual Profiler to show complete traces.
	cudaStatus = cudaDeviceReset();
	if (cudaStatus != cudaSuccess) { fprintf(stderr, "cudaDeviceReset failed!"); return 1; }


	return 0;
}

// Helper function for using CUDA to add vectors in parallel.
cudaError_t addWithCuda(int *c, const int *a, const int *b, unsigned int size)
{
	int *dev_a = 0;
	int *dev_b = 0;
	int *dev_c = 0;
	cudaError_t cudaStatus;


	// Choose which GPU to run on, change this on a multi-GPU system.
	cudaStatus = cudaSetDevice(0);
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaSetDevice failed!  Do you have a CUDA-capable GPU installed?");
		goto Error;
	}

	// Allocate GPU buffers for three vectors (two input, one output)    .
	cudaStatus = cudaMalloc((void**)&dev_c, size * sizeof(int));
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaMalloc failed!");
		goto Error;
	}

	cudaStatus = cudaMalloc((void**)&dev_a, size * sizeof(int));
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaMalloc failed!");
		goto Error;
	}

	cudaStatus = cudaMalloc((void**)&dev_b, size * sizeof(int));
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaMalloc failed!");
		goto Error;
	}

	// Copy input vectors from host memory to GPU buffers.
	cudaStatus = cudaMemcpy(dev_a, a, size * sizeof(int), cudaMemcpyHostToDevice);
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaMemcpy failed!");
		goto Error;
	}

	cudaStatus = cudaMemcpy(dev_b, b, size * sizeof(int), cudaMemcpyHostToDevice);
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaMemcpy failed!");
		goto Error;
	}

	// Launch a kernel on the GPU with one thread for each element.
	addKernel << <1, size >> > (dev_c, dev_a, dev_b);

	// Check for any errors launching the kernel
	cudaStatus = cudaGetLastError();
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
		goto Error;
	}

	// cudaDeviceSynchronize waits for the kernel to finish, and returns
	// any errors encountered during the launch.
	cudaStatus = cudaDeviceSynchronize();
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);
		goto Error;
	}

	// Copy output vector from GPU buffer to host memory.
	cudaStatus = cudaMemcpy(c, dev_c, size * sizeof(int), cudaMemcpyDeviceToHost);
	if (cudaStatus != cudaSuccess) {
		fprintf(stderr, "cudaMemcpy failed!");
		goto Error;
	}

Error:
	cudaFree(dev_c);
	cudaFree(dev_a);
	cudaFree(dev_b);

	return cudaStatus;
}