how can I make this code faster on the GPU?
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Hi.. This is my first experiment with GPU. When I tried to compare the executed time between the cpu and gpu work I found that GPU code take long time . I have an INTEL i5 processor and a NVIDIA 'GeForce GT 740M' with ComputeCapability: '3.5' in my computer, and MATLAB 2013a. I used different size of images but I found same result My current code runs significantly faster on the CPU, even without parfor or spmd, than it does on the GPU. how can I make this faster on the GPU?
The following is CPU code
tic
for i=1:4:size(f,1)
for j=1:4:size(f,2)
gg(i,j)=f(i,j);
end
end;toc
Elapsed time is 0.078421 seconds.
The following is GPU code
ff=gpuArray(f);
tic
for i=1:4:size(ff,1)
for j=1:4:size(ff,2)
gg(i,j)=ff(i,j);
end end;toc
Elapsed time is 1.461808 seconds.
3 Kommentare
Antworten (2)
Anand
am 20 Feb. 2014
There is no operation in the above code that can take advantage of the GPU. All you are doing is looping over every 4th pixel serially. The GPU is well-suited to compute-heavy, parallelizable tasks. In order to take advantage of the GPU in MATLAB, you need to either use functions like arrayfun,<http://www.mathworks.com/help/distcomp/bsxfun.html bsxfun> which will work on multiple elements of the array in parallel or functions that are accelerated for the GPU.
0 Kommentare
Royi Avital
am 21 Feb. 2014
Hopefully, next versions of MATLAB will support OpenCL 2.0. When that happens, CPU and GPU will use the same memory space which will remove the Overhead of GPU Computing.
Assuming using CPU's from AMD which includes GPU which share the same memory with the CPU.
1 Kommentar
Michal
am 3 Mär. 2014
OpenCL support at next MATLAB version?? No way!! Mathworks did not express eny intention to support OpenCL in the near future.
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