NDpar package: Difference between revisions

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Hope it will eventually make it to the parallel package, once its stability is proved.
Hope it will eventually make it to the parallel package, once its stability is proved.
See also the [[Parallel package]] maintained by Olaf Till
See also the [[Parallel package]] maintained by Olaf Till
There is an overhead for parallelization. Hence this package is not suited for very fast functions.


== Installation ==
== Installation ==
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* {{codeline|"ChunksPerProc", 2}} It means that each process should make 2 chunks (2 calls to {{codeline|f}} with {{codeline|"Vectorized", true}}). Increase this number to minimize memory usage for instance. Increasing this number is also useful if function executions can have very different durations. If a process is finished, it can take over jobs from another process that is still busy.
* {{codeline|"ChunksPerProc", 2}} It means that each process should make 2 chunks (2 calls to {{codeline|f}} with {{codeline|"Vectorized", true}}). Increase this number to minimize memory usage for instance. Increasing this number is also useful if function executions can have very different durations. If a process is finished, it can take over jobs from another process that is still busy.


=== Output in cell arrays ===
The following sample code was an answer to [http://stackoverflow.com/questions/27422219/for-every-row-reshape-and-calculate-eigenvectors-in-a-vectorized-way this question]. The goal was to diagonalize matrices. For this example, 2x2 matrices contained as rows of a 2d array (each row of the array being a flattened 2x2 matrix). Note that in this case the function is too fast, so the performance penalty is too high to gain anything.
{{code|diagonalize NxN matrices contained in an array|
<pre>
A = [0.6060168 0.8340029 0.0064574 0.7133187;
0.6325375 0.0919912 0.5692567 0.7432627;
0.8292699 0.5136958 0.4171895 0.2530783;
0.7966113 0.1975865 0.6687064 0.3226548;
0.0163615 0.2123476 0.9868179 0.1478827];
N = 2;
[eigenvectors, eigenvalues] = ndpar_arrayfun(nproc,
                                @(row) eig(reshape(row, N, N)),
                                A, "IdxDimensions", 1, "UniformOutput", false)
</pre>
}}
With {{codeline|"UniformOutput", false}}, the outputs are contained in cell arrays (one cell per slice). In the sample above, both {{codeline|eigenvectors}} and {{codeline|eigenvalues}} are {{codeline|1x5}} cell arrays.


== Issues ==
== Issues ==


Please report any issue using [https://sourceforge.net/p/ndpar/tickets/ tickets].
Please report any issue using [https://sourceforge.net/p/ndpar/tickets/ tickets].
[[Category:External Packages]]

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