Optimize this program on a GPU

Question

Matthias 2013-4-22

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/73074-optimize-this-program-on-a-gpu

I'm trying to speed up my program on a GPU. But it is much slower than the CPU version, although I use a very powerful GPU. I haven't been able to vectorize my code due to the fact that every element in my main vector has to be compared to all the other elements in my main vector. Therefore i had to use a parfor loop.

This is my program:

%%generate data
num_tst = 5000; % this is the key number. The CPU takes about 10 sek for 65000
binning = num_tst/100;
N = num_tst /binning;
timestamps = gpuArray.randi(num_tst,num_tst,1);
detectors = gpuArray.randi(4,num_tst,1);
T = N*binning;
timestamps = sort(timestamps);
%%to be optimized
tic;
correlations = gpuArray.zeros(1,N);
parfor i = 1:(size(timestamps,1)-1)
    a = gpuArray.zeros(1,N);
    j = i+1;
    dts = timestamps(j) - timestamps(i);
    while (dts < T) && (j <= size(timestamps,1))
        if dts == 0 && detectors(i) ~= detectors(j)
            a(1) = a(1) + 2;
        elseif detectors(i) ~= detectors(j)
            dts = floor(dts/binning)+1;
            a(dts) = a(dts) + 1;
        end
        j = j + 1;
        if j <= size(timestamps,1)
            dts = timestamps(j) - timestamps(i);
        end
    end
    correlations = correlations + a;
end
toc;

How can I speed up my program? Is it possible to vectorize a program like this or do I need to implement this program in CUDA code?

2 个评论
显示无隐藏无

Edric Ellis 2013-4-22

You have managed only to run the addition on the GPU, which is why you're seeing no benefit. You should profile the code with no parallelism to see which portions might benefit. If you could make the code self-contained so that it is executable, it might be possible to see how to vectorise or parallelise things.

Matthias 2013-4-22

I thought I parallelised the whole iteration process. Addition and iteration is basically all the program is made of. I edited the code, so that it is executable. The second paragraph is the interesting one.

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Matt J 2013-4-22

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/73074-optimize-this-program-on-a-gpu#answer_83079

编辑：Matt J 2013-4-22

在 MATLAB Online 中打开

Here's a somewhat more vectorized version. The operations you're doing don't seem to be very good candidates for GPU acceleration. Accumarray ops seem hard to accelerate on the GPU, judging from the conspicuous absence of a GPU-accelerated accumarray from MATLAB and all other GPU applications I've seen. However, parfor on the CPU might bring some advantage.

    correlations=zeros(N,1);
    parfor i = 1:(size(timestamps,1)-1)
        dts=timestamps(i+1:end)-timestamsp(i);
        val=detectors(i+1:end)~=detectors(i) & dts<T;
          val=val+val&(dts==0);
        subs=floor(dts/binning)+1;
        a=accumarray(subs(:),val(:),[N,1]);
        correlations = correlations + a;
    end
   correlations=correlations.';

8 个评论
显示 6更早的评论隐藏 6更早的评论

Matthias 2013-4-22

编辑：Matthias 2013-4-22

I found my Error. The fake data I generated was false. Thank you!

Matt J 2013-4-22

在 MATLAB Online 中打开

If I'm not mistaken the expression ALL(MAX(SUBS)<=SZ) will only be true, if max(subs) <= 1

No, it requires all(max(subs)<=N). Here are some examples to illustrate the issue

    >> X=accumarray([1;2;2;2;3;3],true,[10,1]); X'
    ans =
         1     3     2     0     0     0     0     0     0     0

but

    >> X=accumarray([1;2;2;2;3;30],true,[10,1]); X'
    Error using accumarray
    First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).

请先登录，再进行评论。