Appropriate usage of Parallel Pool

2020 6 7
2 个回答
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更新时间：2020 6 11
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1 个投票

Hi. I have two related questions:
Question 1: Which of the following 4 is best to use in order to take advantage of my PC's multi-core setup? Or if instead any other method would be more appropriate (e.g. using gcp), please let me know. Methods 1&2 are identical to 3&4 with the exception of how I have treated the loop: 'for' vs 'parfor'.
Question 2: My PC also has a NVIDIA Quadro P3200 GPU. Could you please possibly also provide an additional script (for the same CV-lasso setup) potentially utilising the GPU, too?
%Method 1
for i = 1:10
pool = parpool('local',5)
opts = statset('UseParallel',true);
b = lasso(X(:,:,i),y,'CV',10,'Options',opts);
delete(pool)
end
%Method 2
pool = parpool('local',5)
for i = 1:10
opts = statset('UseParallel',true);
b = lasso(X(:,:,i),y,'CV',10,'Options',opts);
end
delete(pool)
%Method 3
parfor i = 1:10
pool = parpool('local',5)
opts = statset('UseParallel',true);
b = lasso(X(:,:,i),y,'CV',10,'Options',opts);
delete(pool)
end
%Method 4
pool = parpool('local',5)
parfor i = 1:10
opts = statset('UseParallel',true);
b = lasso(X(:,:,i),y,'CV',10,'Options',opts);
end
delete(pool)
Thank you for your time and help!
PS: Btw, I wrote my GPU model (not to show off, but) just in case some tech-savvy pal says something like 'Your GPU is not powerful enough, and it's not worth the trouble. Stick to utilising your multi-core setup, instead'. I am really looking for the strategy that provides me with the lowest possible runtime given the resources.

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Haris K.
Haris K. 2020-6-7
My intuition says that there would be added benefit when using both UseParallel and parfor, since the former treats the CV & lambda iterations in parallel, while the latter treats the iterations over X in parallel. But basically, with my question, I wanted to clarify whether or not there are any complications when using both.
Let's wait to see if anyone else can further add to the discussion.

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 采纳的回答

Haris K.
Haris K. 2020-6-11
编辑：Haris K. 2020-6-11

1 个投票

Just in case someone finds this comparison helpful. I changed the methods a bit, as I realized that it is not a good practise to delete the pool inside the loop. I also added the no-parallel case below (-this is Method 4, now). The exact code and the respective times are shown below:
clear
N=30;
T=1000;
y = randn(T,1);
X = rand(T,80,N);
for j=1:10
%Method 1
tic
pool = parpool('local',6);
for i = 1:N
opts = statset('UseParallel',true);
b = lasso(X(:,:,i),y,'CV',10,'Options',opts);
end
delete(pool)
tau(j,1)=toc;
%Method 2
tic
pool = parpool('local',6);
parfor i = 1:N
b = lasso(X(:,:,i),y,'CV',10);
end
delete(pool)
tau(j,2)=toc;
%Method 3
tic
pool = parpool('local',6);
parfor i = 1:N
opts = statset('UseParallel',true);
b = lasso(X(:,:,i),y,'CV',10,'Options',opts);
end
delete(pool);
tau(j,3)= toc;
%Method 4
tic
for i = 1:N
b = lasso(X(:,:,i),y,'CV',10);
end
tau(j,4)= toc;
end
mean(tau)
The results were:
ans =
51.6030 33.5555 34.2442 82.0831

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Matt J
Matt J 2020-6-11
编辑：Matt J 2020-6-11
You probably shouldn't include the time to create and delete the pool within the tic...toc. It adds a lot of overhead that you wouldn't normally incur - you wouldn't normally re-create the pool every time you wanted to re-run a set of parallel jobs.
Haris K.
Haris K. 2020-6-11
You are absolutely right, but the loop over j is part of the 'test', in the sense that what I am interested in measuring is how long the i-loop is taking to run. And instead of giving out a single time figure for each method, i.e. j=1 (- reflecting one-off forces that might have positively or negatively affected my runtime, such as an open browser doing processes and stuff in the background), I thought it would be a better idea to run it 10 times and take the average.
Also let me take the chance to thank you for your helpful comments, here (and also to many-many other eye-openning posts of yours that have helped me throughout the years). Cheers Matt!
Matt J
Matt J 2020-6-11
You are quite welcome.

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更多回答（1 个）

Matt J
Matt J 2020-6-7
编辑：Matt J 2020-6-7

1 个投票

Question 1: Which of the following 4 is best to use
I'm sure it depends on the dimensions of X(:,:,i), but here's what I would try first,
pool = parpool('local',5)
opts = statset('UseParallel',true);
clear b
for i = 10:-1:1
b{i} = lasso(X(:,:,i),y,'CV',10,'Options',opts);
end
I would probably then compare that to parfor without UseParallel
parfor i = 1:10
b{i} = lasso(X(:,:,i),y,'CV',10);
end
Question 2: My PC also has a NVIDIA Quadro P3200 GPU. Could you please possibly also provide an additional script (for the same CV-lasso setup) potentially utilising the GPU, too?
It doesn't look like lasso() supports gpuArray input, unfortunately.

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Haris K.
Haris K. 2020-6-7
编辑：Haris K. 2020-6-7
I simplified the indexing on my matricies so that to post my issue here, and forgot to correct the subscripts on X. Thanks for letting me know Matt. I have now editted it [X(i) was meant to be X(:,:,i)], and it should make sense.
Haris K.
Haris K. 2020-6-7
编辑：Haris K. 2020-6-7
Is there a reason why you wouldn't use both UseParallel and parfor?
Matt J
Matt J 2020-6-7
编辑：Matt J 2020-6-7
Mostly just intuition. If you have enough work in each call to lasso() to keep a core busy, I don't know why it would be beneficial to try even more parallel splitting. But ultimately, experimentation is the only way to know which strategy is optimal.

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