ANN: LAPACK and ScaLAPACK new functionality survey

[cross-posted to a few groups with relevant experience / ideas.
watch those follow-ups.]


LAPACK and ScaLAPACK new functionality survey


We plan to update the LAPACK and ScaLAPACK libraries and would like to
have feedback from users on what functionalities they think are
missing and would be needed in order to make these libraries more
useful for the community. We invite you to enter your suggestions in
the form below. It would be most useful to have input by June 16th,
although we would welcome your input at any time.


Both LAPACK and ScaLAPACK provide well-tested, open source, reviewed
code implementing trusted algorithms that guarantee reliability,
efficiency and accuracy. Any new functionality must adhere to these
standards and should have a significant impact in order to justify the
development costs. We are also interested in suggestions regarding
user interfaces, documentation, language interfaces, target (parallel)
architectures and other issues, again provided the impact is large
enough.


We already plan to include a variety of improved algorithms discovered
over the years by a number of researchers (e.g. faster or more
accurate eigenvalue and SVD algorithms, extra precise iterative
refinement, recursive blocking for some linear solvers, etc.). We also
know of a variety of other possible functions we could add
(e.g. updating and downdating factorizations), but are uncertain of
their impact.


Please see http://icl.cs.utk.edu/lapack-survey.html for the survey.
We would like to have your input by June 16th, 2004.


Regards,
Jack Dongarra, Jim Demmel, and Sven Hammarling
--

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