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From "John Mulcahy (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MATH-223) QRDecomposition can easily be made to run about twice as fast
Date Wed, 03 Sep 2008 10:23:44 GMT

    [ https://issues.apache.org/jira/browse/MATH-223?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12627955#action_12627955
] 

John Mulcahy commented on MATH-223:
-----------------------------------

2.0 branch version looks good, can use the same transposed qr there including for the new
solve routines to have the loops iterate over rows of the transposed matrix. Bear in mind
that BLAS and LAPACK tend to assume column-major storage so for Java implementations it can
be more efficient to change the algorithms so that 2D matrices are stored as their transposes
and their indices are swapped within the algorithm. Plenty of scope for typos when doing that
though :)

> QRDecomposition can easily be made to run about twice as fast
> -------------------------------------------------------------
>
>                 Key: MATH-223
>                 URL: https://issues.apache.org/jira/browse/MATH-223
>             Project: Commons Math
>          Issue Type: Improvement
>    Affects Versions: 1.2
>         Environment: Any
>            Reporter: John Mulcahy
>            Priority: Minor
>         Attachments: QRDecompositionImpl.java
>
>
> The QRDecomposition will run much faster (about twice as fast) if the qr and Q matrices
are calculated as their transposes and the transposition is sorted out in the getQ() method.
Using the transposes allows the loops to iterate over rows of the transposed matrices rather
than columns. It might also be useful to cache the Q matrix locally when it is generated in
case there are any subsequent calls to getQ() as this is the most expensive part of the decomposition.

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