How do I allocate and transfer(to and from Host) 2D arrays in device memory in Cuda?
I found a solution to this problem. I didn't have to flatten the array.
The inbuilt cudaMallocPitch()
function did the job. And I could transfer the array to and from device using cudaMemcpy2D()
function.
For example
cudaMallocPitch((void**) &array, &pitch, a*sizeof(float), b);
This creates a 2D array of size a*b with the pitch as passed in as parameter.
The following code creates a 2D array and loops over the elements. It compiles readily, you may use it.
#include<stdio.h>
#include<cuda.h>
#define height 50
#define width 50
// Device code
__global__ void kernel(float* devPtr, int pitch)
{
for (int r = 0; r < height; ++r) {
float* row = (float*)((char*)devPtr + r * pitch);
for (int c = 0; c < width; ++c) {
float element = row[c];
}
}
}
//Host Code
int main()
{
float* devPtr;
size_t pitch;
cudaMallocPitch((void**)&devPtr, &pitch, width * sizeof(float), height);
kernel<<<100, 512>>>(devPtr, pitch);
return 0;
}
Flatten it: make it one-dimensional. See how it's done here
Your device code could be faster. Try utilizing the threads more.
__global__ void kernel(float* devPtr, int pitch)
{
int r = threadIdx.x;
float* row = (float*)((char*)devPtr + r * pitch);
for (int c = 0; c < width; ++c) {
float element = row[c];
}
}
Then you calculate the blocks and threads allocation appropriate so that each thread deals with a single element.
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