| Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
|---|---|---|
| Article Number | 05004 | |
| Number of page(s) | 8 | |
| Section | T5 - Software development | |
| DOI | https://doi.org/10.1051/epjconf/201921405004 | |
| Published online | 17 September 2019 | |
https://doi.org/10.1051/epjconf/201921405004
Performance Analysis of Effective Symbolic Methods for Solving Band Matrix SLAEs
Joint Institute for Nuclear Research, Laboratory of Information Technologies,Joliot-Curie 6,
141980, Dubna, Moscow region, Russia
* e-mail: milena.p.veneva@gmail.com
** e-mail: ayriyan@jinr.ru
Published online: 17 September 2019
This paper presents an experimental performance study of implementations of three symbolic algorithms for solving band matrix systems of linear algebraic equations with heptadiagonal, pentadiagonal, and tridiagonal coefficient matrices. The only assumption on the coefficient matrix in order for the algorithms to be stable is nonsingularity. These algorithms are implemented using the GiNaC library of C++ and the SymPy library of Python, considering five different data storing classes. Performance analysis of the implementations is done using the high-performance computing (HPC) platforms “HybriLIT” and “Avitohol”. The experimental setup and the results from the conducted computations on the individual computer systems are presented and discussed. An analysis of the three algorithms is performed.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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