MINRES-QLP Pack and Reliable Reproducible Research via Supportable Scientific Software
DOI:
https://doi.org/10.5334/jors.bbAbstract
The MINRES-QLP Pack is a suite of standard and extended Krylov subspace methods for solving large linear systems and linear least-squares problems in which the coefficient matrices are potentially singular or ill-conditioned and possibly have special symmetries. Our purpose is to develop robust open-source MATLAB implementations of these algorithms that are faithful to the theory, following the philosophy of reproducible research (RR), and practicing development principles of what we call supportable scientific software (SSS) that promote reliable reproducible research (RRR). In this paper, we review key features in the ongoing theoretical and software development of our algorithms in the MINRES-QLP Pack. We highlight the most effective software engineering tools known to us that are potentially useful to other scientific research areas. We support open calls to create more incentives for practitioners of robust and reliable scientific software such as citations and grants for quality software. We encourage introducing principles of RRR via SSS to computational science students in advanced courses of scientific computing and to computational scientists through seminars, workshops, or conferences. To these ends, we started an experimental seminar course, “Reliable Mathematical Software” (IIT MATH-573) in our institution, and organized multiple sessions on “Reliable Computational Science” in the SIAM Annual Meeting 2014. We share our research practice and pedagogic experiences in this article.
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