从主机到设备的CUDA传输2D阵列 [英] CUDA-transfer 2D array from host to device
本文介绍了从主机到设备的CUDA传输2D阵列的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我主要是2D矩阵。我要从主机转移到设备。您能告诉我如何分配内存并将其传输到设备内存吗?
I have a 2D matrix in the main. I want to transfer if from host to device. Can you tell me how I can allocate memory for it and transfer it to the device memory?
#define N 5
__global__ void kernel(int a[N][N]){
}
int main(void){
int a[N][N];
cudaMalloc(?);
cudaMemcpy(?);
kernel<<<N,N>>>(?);
}
推荐答案
也许
#define N 5
__global__ void kernel(int *a)
{
// Thread indexing within Grid - note these are
// in column major order.
int tidx = threadIdx.x + blockIdx.x * blockDim.x;
int tidy = threadIdx.y + blockIdx.y * blockDim.y;
// a_ij = a[i][j], where a is in row major order
int a_ij = a[tidy + tidx*N];
}
int main(void)
{
int a[N][N], *a_device;
const size_t a_size = sizeof(int) * size_t(N*N);
cudaMalloc((void **)&a_device, a_size);
cudaMemcpy(a_device, a, a_size, cudaMemcpyHostToDevice);
kernel<<<N,N>>>(a_device);
}
您可能会错过的要点是,当您静态声明这样的数组时 A [N] [N]
,它实际上只是一个行主要指令段线性存储器。编译器在 a [i] [j]
和 a [j + i * N]
之间自动转换发出代码。在GPU上,您必须使用第二种访问方式来读取从主机复制的内存。
The point you might have missed is that when you statically declare an array like this A[N][N]
, it is really just a row major ordered piece of linear memory. The compiler is automatically converting between a[i][j]
and a[j + i*N]
when it emits code. On the GPU, you must use the second form of access to read the memory you copy from the host.
这篇关于从主机到设备的CUDA传输2D阵列的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!
查看全文