How to construct a Sliced Reduction Variable in MALTAB parallel for loop

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Hello all, I am having a code with the following construction. In this code, I need to extract K (M x M) from the parfor as this will save much time. Currently, I am working on it using ordinary for loop.
... % code
K = zeros(M,M);
parfor i = 1:N
k = ... % k is a matrix of dimensions (m x m) created in each pafor iteration.
u = ... % u is a vector of integers (n x 1) created in each pafor iteration.
K(u,u) = K(u,u) + k; % This line returns back an error message.
end
... % code
Is there anyway to re-write the code to be accepted in parfor loop without changing the calculation methodology. In a more general form, how can I involve a sliced reduction variable (K in this case) in parfor loop?
Thanks all and best Ahmad

回答(2 个)

Jeff Miller
Jeff Miller 2017-11-20
Maybe something like this?
k = cell(N,1);
u = cell(N,1);
parfor i = 1:N
k{i} = ... % k is a matrix of dimensions (m x m) created in each pafor iteration.
u{i} = ... % u is a vector of integers (n x 1) created in each pafor iteration.
end
K = zeros(M,M);
for i = 1:N
K(u{i},u{i}) = K(u{i},u{i}) + k{i};
end
  1 个评论
Ahmad Gad
Ahmad Gad 2017-11-20
Hi Jeff, thanks for the answer.
I already isolated them in two different loops as you said. But my question was how to combine them all in a one parallel loop.
Thanks and best Ahmad

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Edric Ellis
Edric Ellis 2017-11-21
parfor doesn't support the notion of a variable that is both sliced and reduced. You need to recast things so that you have either a pure sliced or a pure reduced output. Here's one way that you might be able to achieve that - I'm not sure if I've completely understood your example, but perhaps this should give you sufficient information to continue:
m = 4;
n = 3;
K = zeros(m, m);
parfor idx = 1:n
% build 'k' and 'u' as per the example
k = idx .* ones(m, m);
u = (1:n)';
% Build an m-by-m increment
increment = zeros(m, m);
increment(u, u) = k(u, u);
% Ensure 'K' is a pure reduction variable
K = K + increment;
end
  1 个评论
Ahmad Gad
Ahmad Gad 2017-11-27
Hello Edric;
I had previously implemented a similar method, but for very big matrices (such as my cases), adding matrices many times always kills MATLAB. I am trying my best to avoid your final line
K = K + increment;
From my main example, M = 300k, N = 100k, m = n = 450
Thank you!

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