Updated 23 Oct 2006
For users with a heterogeneous network of computers with a common file system and a problem that lend itself to parallelization these functions might be of help. Such problems may be finite difference calculations of gradients, parametric studies or iterative solutions of equation systems. Say, for instance, that you have 20 large eigenvalue problems that you want to solve in parallel.
Then the code is:
A=rand(500,500,20);% Generate 20 500x500 matrices
d=paralize('eig',A);% Solve with eig in parallel
It is as simple as that, provided you have started the servers. Servers are started with the MATLAB command serve. Could it be more easy?
HTML-files describe the use in more detail.
Thomas Abrahamsson (2023). paralize (v2006a) (https://www.mathworks.com/matlabcentral/fileexchange/211-paralize-v2006a), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
Inspired: jPar - parallelizing Matlab calculations on multicores and in clusters without file communication
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This old contribution (from 1997) needed an overhaul. It now supports versions of Matlab up to 7.2 thanks to my soulmate Andrzej Karbowski, Warsaw.