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