Hi everyone,

Just trying to deduce a plan to attack a problem of mine, the basis of which is a tiny project to be done by young slave/intern doing a singular value decomposition (SVD) routine in Chapel. Nothing special, it is primary targetted at small matrices, those that define the relationship between stress and strain. This means that numerical issues with SVD and large matrices are less critical.

With respect to advanced linear algebra libraries available for use within one's own code, Chapel has several options.

Both BLAS and LAPACK are wrappers around ??? and LAPACK respectively. This is great if you just want to exploit such a library. But wrappers make the retrofitting of advances in low level routines such as Edward Anderson's (2018 ACM TOMS) improved vector norm a non-trivial task.

The Jama port to Chapel is simple but not very extensive.

I have not gone too deeply into the LinearAlbegra project - yet. Maybe next week.

From a philsophical standard, as opposed to the practicality of getting a
program going, isn't Chapel the sort of language that one would want to use to write such libraries? In doing so, you might want to look at what is being done in PLASMA.

        https://bitbucket.org/icl/plasma

See also the work on LAPACK's cousin??, PLASMA which is a software package for solving problems in dense linear algebra using multicore processors & Xeon Phi coprocessors. PLASMA provides implementations of state-of-the-art algorithms using cutting-edge task scheduling techniques. PLASMA currently offers a collection of routines for solving linear systems of equations, least squares problems, eigenvalue problems, and singular value problems. PLASMA is in the process of porting form QUARK to OpenMP. I would have thought that PLASMA written in Chapel would have been an interesting comparison to this almost (??) complete alternative in OpenMP.

Regards - Damian

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