Copying a few floating numbers to the Shared memory

Hi ,
I have 512512=262144 pixels and I want to do the same process for all of them. So, I run a kernel for this. The process needs the coordinates of the pixels, so I need to transfer X_Coordinates (1512) and Y_Coordinates (1*512) of the pixels to the device. if i do it normally, then it goes to the global memory and all the threads need to read from it. However, if i transfer it to the shared memory, then my kernel will be much faster i guess.
I know how do store data on the dynamic shared memory:
"
if (TID < 512 )
{

SharedMemory_XCoordinates [TID] = X_Coordinates [TID];
SharedMemory_YCoordinates [TID] = Y_Coordinates [TID];
}
__syncthreads(); "

This is the normal way, but does not make sense to me because if i do this, I hold 262144 threads for only 512 numbers,!! This highly imposes latency in my Kernel (what i want to do after the __syncthreads()). So, the question is how i can store the X_Coordinates and Y_Coordinates on the shared memory efficiently?

Thanks,
Moein.

Buffering data in shared memory can make sense if there is data re-use. Your description suggests that for your use case the data processing is of a streaming nature without any data re-use, in which case shuffling data through shared memory will at best have no performance impact but likely will slow down the processing.

Hi,
Well, i did not put all of the code of my kernel here, but I have multiple Kernels in my program and I’ll be using Y_Coordinates and X_Coordinates in all of them. So, the memory indicated by these two pointers will be repeatedly used in my kernel(s).

does it make sense to run a kernel with 1024 hreads to transfer the Y_Coordinates and X_Coordinates to the shared memory at the beginning of my program and then use them in other Kernels?

Moein.

You can buffer data in shared memory for the duration of a kernel. You cannot use shared memory to transport data between kernels.

Ok. So, is there any solution for my first question?

It is not clear to me what your first question is.

No sure I fully understand the requirements, but on the face of it, sounds like constant memory would be the place to store them.

Later: To elaborate:

__constant__ float c_X_coord[512];
__constant__ float c_Y_coord[512];

__global__
void kernel_1(...){
	do things with c_X_coord
	do things with c_Y_coord
}
		
__global__
void kernel_2(...){
	do things with c_X_coord
    do things with c_Y_coord
}
		
		
cudaMemcpyToSymbol(c_X_coord, hostDataX, 512*sizeof(float));
cudaMemcpyToSymbol(c_Y_coord, hostDataY, 512*sizeof(float));

kernel_1<<<...>>>
kernel_2<<<...>>>