MULTICORE Matlab script

Publisher review:
MULTICORE provides some functions realizing parallel processing on multiple cores/machines The latest Matlab releases (starting with R2007a) include support for multiple cores. However, Matlab will only take advantage of multiple cores in evaluating certain computations like an FFT or a FIR filtering operation. Matlab will never be able to determine if, for example, consecutive function calls in a for-loop are independent of each other.With this package, I provide some MATLAB-functions realizing parallel processing on multiple cores on a single machine or on multiple machines that have access to a common directory.If you have multiple function calls that are independent of each other, and you can reformulate your code as resultCell = cell(size(parameterCell));for k=1:numel(parameterCell)resultCell{k} = myfun(parameterCell{k});endthen, replacing the loop byresultCell = startmulticoremaster(@myfun, parameterCell);allows you to evaluate your loop in parallel in several processes. All you need to do in the other Matlab processes is to runstartmulticoreslave;No special toolboxes are used, no compilation of mex-files is necessary, everything is programmed in plain and platform-independent Matlab. If one of your slave processes dies - don't care, the master process will go on working on the given task.Please consider that the communication between the processes, which is done by using the file system, causes some overhead. Thus, you will only notice an improvement in speed if your function calls need considerable time, let say some seconds. However, if you have a huge number of function evaluations to be executed, where every function evaluation only needs a fraction of a second, you can still use this package. You will just have to write a small adapter function that gathers a number of function evaluations and let the multicore package parallelize the execution of that adapter function.Note: The Matlab multithreading capability (R2007a and higher) might terminate all the advantage gained by using the multicore package. So make sure that you UNcheck "Enable multihreaded computation" under File/Preferences/General/Multithreading in all involved Matlab sessions. Keywords: Parallel processing, distributed computing, multiple core. Requirements: · MATLAB Release: R2006b
Operating system:
Windows / Linux / Mac OS / BSD / Solaris

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