How to make sure that function is entirely run on GPU?

I want to implement an algorithm, which performs operations on very large arrays (up to 10 million entries each), on the GPU. I have already achieved, that it runs on the GPU and even gives a speed up of up to factor 10, but I am not entirely sure, whether all operations and functions of the algorithm are running on the GPU, or whether there is still CPU-GPU transfers required. Specifically, I wonder whether Matlab offers an intuitive way of showing such unnecessary transfers.

So my question is whether the following operation b leads to such transfers:

If I define two variables amplitude and period on the CPU - let's say

amplitude=300;

period=3;

and create an gpu array

u=rand(10000000,1);

and calculate b by using the function

b = @(u) b_st+amplitude*sin(u*2*pi/period);

will then

x=b(u);

be calculated entirely on the GPU? Or do I have to also define period and amplitude on the GPU via gpuarray()?

Thank you in advance!

Answer 1

[Edric Ellis]

Operations on gpuArray data automatically take place on the GPU. When you operate on mixed GPU and CPU data, generally the operation takes place on the GPU - the only time this is not the case is when the gpuArray inputs are considered to be "parameters" (such as sizes or dimensions) rather than "data". For example:

sum(magic(3), gpuArray(1))

In this case, the "data" argument to sum is on the CPU, and the dimension "parameter" happens to be on the GPU. Because the data is on the CPU, the GPU-ness of the summation dimension is ignored, and the compuation takes place on the CPU.