Question

I m trying to use the parfor loop in the matlab parallelism package. I m having a similar problem to this guy : MATLAB parfor slicing issue? . The output matrix doesn t seem to be recognized as a sliced variable. In my specific case, I m trying to stack use other for loops inside the parfor, and I have trouble applying the solution proposed in the other thread to my problem. Here is a dummy example of what I m trying to do :

n=175;
matlabpool;

Matred=zeros(n,n);

Matx2Cell = cell(n);

parfor i=1:n
    for j=1:n
        for k=1:n

            Matred(j,k)=exp((j+i+k)/500)
        end;
    end;
    Matx2Cell{i}=Matred;

end;
matlabpool close;

P.S.,我知道,它将努力将 par子放在 k上,而不是一lo。但是,我仍然想把它放在一路上(我认为,在我的真正方案中,这样做会更具有时间效率)。

Thanks a lot Frédéric Godin

Answer 1

您可以将<条码>Matred = 零s(n); 放入教区,但这非常缓慢。而是用<代码>Matred = 零s(n);界定职能:实际上相同,但速度更快:

function Matred = calcMatred(i,n)
Matred=zeros(n);
for j=1:n
    for k=1:n
        Matred(j,k)=exp((j+i+k)/500);
    end
end

时间比较:

matlabpool
n = 175;
Matx2Cell = cell(n,1);

tic
parfor i=1:n
    Matred=zeros(n);
    for j=1:n
        for k=1:n
            Matred(j,k)=exp((j+i+k)/500);
        end
    end
    Matx2Cell{i}=Matred;
end
toc

tic
parfor i=1:n
    Matx2Cell{i}=calcMatred(i,n);
end
toc

matlabpool close

在我的机器上,头一台需要7秒,第二次需要0.3秒。

请注意,I ve更改了<代码>Matx2Cell至cell(n,1),因为cell(n) 做了n x n 手机阵列。

Answer 2

你们需要把马塔德迁入 par院。之所以需要这样做,是因为每 par一堂,都需要一份新版的马塔德。

n=175;
matlabpool;

Matx2Cell = cell(n);

parfor i=1:n
    Matred=zeros(n,n);
    for j=1:n
        for k=1:n

            Matred(j,k)=exp((j+i+k)/500)
        end;
    end;
    Matx2Cell{i}=Matred;

end;
matlabpool close;

友情链接