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Performance Analysis of Effective Symbolic Methods for Solving Band Matrix SLAEs

机译:解决带矩阵销售的有效符号方法的性能分析

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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.
机译:本文介绍了三种符号算法的实现的实验性能研究,该算法用于求解带七对角,五对角和三对角系数矩阵的线性代数方程的带矩阵系统。为了使算法稳定,对系数矩阵的唯一假设是非奇异性。考虑到五个不同的数据存储类,使用C ++的GiNaC库和Python的SymPy库实现了这些算法。使用高性能计算(HPC)平台“ HybriLIT”和“ Avitohol”对实现进行性能分析。介绍并讨论了实验设置以及在单个计算机系统上进行的计算结果。对这三种算法进行了分析。

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