https://www.cnblogs.com/xudong-bupt/p/3461163.html
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#include <stdio.h>
#include<cuda_runtime.h>
//__global__声明的函数，告诉编译器这段代码交由CPU调用，由GPU执行
__global__
void
add(
const
int
*dev_a,
const
int
*dev_b,
int
*dev_c)
{
int
i=threadIdx.x;
dev_c[i]=dev_a[i]+dev_b[i];
}
int
main(
void
)
{
//申请主机内存，并进行初始化
int
host_a[512],host_b[512],host_c[512];
for
(
int
i=0;i<512;i++)
{
host_a[i]=i;
host_b[i]=i<<1;
}
//定义cudaError，默认为cudaSuccess(0)
cudaError_t err = cudaSuccess;
//申请GPU存储空间
int
*dev_a,*dev_b,*dev_c;
err=cudaMalloc((
void
**)&dev_a,
sizeof
(
int
)*512);
err=cudaMalloc((
void
**)&dev_b,
sizeof
(
int
)*512);
err=cudaMalloc((
void
**)&dev_c,
sizeof
(
int
)*512);
if
(err!=cudaSuccess)
{
printf
(
"the cudaMalloc on GPU is failed"
);
return
1;
}
printf
(
"SUCCESS"
);
//将要计算的数据使用cudaMemcpy传送到GPU
cudaMemcpy(dev_a,host_a,
sizeof
(host_a),cudaMemcpyHostToDevice);
cudaMemcpy(dev_b,host_b,
sizeof
(host_b),cudaMemcpyHostToDevice);
//调用核函数在GPU上执行。数据较少，之使用一个Block，含有512个线程
add<<<1,512>>>(dev_a,dev_b,dev_c);
cudaMemcpy(&host_c,dev_c,
sizeof
(host_c),cudaMemcpyDeviceToHost);
for
(
int
i=0;i<512;i++)
printf
(
"host_a[%d] + host_b[%d] = %d + %d = %d\n"
,i,i,host_a[i],host_b[i],host_c[i]);
cudaFree(dev_a);
//释放GPU内存
cudaFree(dev_b);
//释放GPU内存
cudaFree(dev_c);
//释放GPU内存
return
0 ;
}
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