Improving speed in construction of a matrix

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Hi.
Im currently implementing a code, where part of the code constructs a matrix several million times. Currently, the construction of this matrix takes much more time, than the actual computing invovled with the matrix. Its a rather simple matrix, but takes a third of the total runtime. I want to construct it faster, but cant seem to bring the time down. Ive tried two approaches.
One implementation:
B = zeros(9,9);
B(1:3,1) = A(1,:);
B(4:6,2) = A(1,:);
B(7:9,3) = A(1,:);
B(1:3,4) = A(2,:);
B(4:6,5) = A(2,:);
B(7:9,6) = A(2,:);
B(1:3,7) = A(3,:);
B(4:6,8) = A(3,:);
B(7:9,9) = A(3,:);
And the other implementation:
Z = zeros(3,1);
B =[A(:,1) Z Z A(:,2) Z Z A(:,3) Z Z
Z A(:,1) Z Z A(:,2) Z Z A(:,3) Z
Z Z A(:,1) Z Z A(:,2) Z Z A(:,3)];
Both giving a inaduqate execution time. Is there a faster way to construct this type of matrix?
  6 Comments
Matt J
Matt J on 16 Jan 2024
Edited: Matt J on 16 Jan 2024
I think it unlikely you are going to be able to reliably optimize such an infinitessimal task in MCode. Different computers will give you different relative performance. You need to try to reorganize your computation in large vectorized batches.
cTroels
cTroels on 16 Jan 2024
I was able to bring the execution time of the function down to 4s by just writing out the whole matrix explicitly. Should have done that initially i guess. But thanks for the suggestions! Appreciate the inputs.

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Accepted Answer

Benjamin Thompson
Benjamin Thompson on 20 Jan 2024
Not sure where your data for A is coming from, or where the output of B is going to. if each A -> B mapping is independent try parfor if you have a multicore processor or using a gpuArray.

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