在GPU上加速图像处理算法，并行处理Matlab

Question

I want to accelerate my algorithm because I need to run it on hundreds of images,so I tried to use unvectorized GPU code, running the same code on GPU, I have nvidia Geforce GT 650M with 2 GB on my PC, however it was very slow than the CPU version. After searching I am convinced to pass to vectorized GPU code using batch process (pagefun, bsxfun), I tried so much to solve this problem without a solution. can someone help me about this code:

Q=100;
       for i=3:n-2
        for j=3:m-2 
         A(i,j)=0;
            for c=1:Q
                        if B(i,j,c)~=0
                        A(i,j)=A(i,j)+(-(B(i,j,c)).*log(B(i,j,c)));
                        end
            end
        end
       end

Another question Why Matlab uses just 20% of my CPU? How I can take benefits of my CPU to accelerate my processing

Is Matlab a single threaded app?

Thanks in advance

Answer 1

The vectorized version is this:

BB = B(3:(n-2),3:(m-2),:);
cutoff = 10^(-6);
logBB = log(BB);
logBB(BB<cutoff) = 0; % remove divergent terms
A = -sum(BB.*logBB,3);

This should already run much faster even on a CPU. If you have a GPU, all you need to do is have the input array

BB = gpuArray(BB);

stored on the GPU, and then collect the results

A = gather(A);

back to the CPU

Answer 2

You will need to buy the parallel computing toolbox . (using parfor).

This is a well known limitation of matlab where some of the underlying functions do not paralellize across multiple cores (not threads). A quick ballpark is to look at how much CPU matlab uses and multiply that by the number of COREs you have in your pc (this should get you to somewhere around 100%).

If you want to utilize your computers GPU, parallel computing toolbox is the only way to do so.

From mathworks

This really depends on what you are doing. For some code MATLAB can only utilize a single core of a single processor, for other code, MATLAB will automatically utilize all available cores (and maybe processors). It really depends on the underlying functions. Some things cannot be easily parallelized. Sometimes you can help MATLAB with things like parfor loops. Other times you might need something like MPI. Still other times there really is nothing you can do.