What is the fastest way to do repeated element wise matrix multiplication?
16 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
Aravind Varma Dantuluri
le 19 Fév 2024
Commenté : Aravind Varma Dantuluri
le 19 Fév 2024
Given a matrix `A`, I need to multiply with another constant vector `B`, N times (N > 1 million). The size of `A` is `9000x1` and `B` is `9000x1000`.
The code is currently evaluated in the following way (random values taken for example):
B = rand(9000,1000); % B is fixed, does not depend on i
N = 1000000;
for i=1:N
rand('seed',i);
A = rand(9000,1); % A is 9000x1 matrix which varies with i
% prod = A.*B; % prod is 9000 x 1000 matrix
% sum_temp = sum(product); % sum_temp is 1 x 1000 matrix
% Edit
sum_temp = A.' * B;
% do multiple pperations with sum_temp
% result(i) = some_constant;
end
I used Profiler to see which line is taking the most time and it is the 2nd line (prod = A.*R;). The problem is that N is very large and the code is taking over several days to complete.
I am about to try the parallel computing toolbox (GPU computing), but are there any suggestions on what I can do in the basic version?
How can I reduce the run-time of such codes in MATLAB?
0 commentaires
Réponse acceptée
Stephen23
le 19 Fév 2024
Déplacé(e) : Stephen23
le 19 Fév 2024
Reduce the number of operations inside the loop by replacing TIMES and SUM with MTIMES (of course adjusting the matrix/vector orientations to suit).
5 commentaires
Stephen23
le 19 Fév 2024
Modifié(e) : Stephen23
le 19 Fév 2024
@Aravind Varma Dantuluri: did that make enough difference to the speed?
Another possibilty would be to look at some kind of parallel processing:
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Logical dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!