Improvements to SLEPc in Releases 3.14–3.18

IF 2.7 1区 数学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING ACM Transactions on Mathematical Software Pub Date : 2023-06-07 DOI:https://dl.acm.org/doi/10.1145/3603373
Jose E. Roman, Fernando Alvarruiz, Carmen Campos, Lisandro Dalcin, Pierre Jolivet, Alejandro Lamas Daviña
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引用次数: 0

Abstract

This short paper describes the main new features added to SLEPc, the Scalable Library for Eigenvalue Problem Computations, in the last two and a half years, corresponding to five release versions. The main novelty is the extension of the SVD module with new problem types such as the generalized SVD or the hyperbolic SVD. Additionally, many improvements have been incorporated in different parts of the library, including contour integral eigensolvers, preconditioning and GPU support.

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版本3.14-3.18对SLEPc的改进
这篇短文描述了在过去两年半的时间里,SLEPc(特征值问题计算的可扩展库)增加的主要新功能,对应于五个发布版本。主要新颖之处在于将奇异值分解模块扩展为新的问题类型,如广义奇异值分解或双曲奇异值分解。此外,许多改进已经纳入到库的不同部分,包括轮廓积分特征求解器,预处理和GPU支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Transactions on Mathematical Software
ACM Transactions on Mathematical Software 工程技术-计算机:软件工程
CiteScore
5.00
自引率
3.70%
发文量
50
审稿时长
>12 weeks
期刊介绍: As a scientific journal, ACM Transactions on Mathematical Software (TOMS) documents the theoretical underpinnings of numeric, symbolic, algebraic, and geometric computing applications. It focuses on analysis and construction of algorithms and programs, and the interaction of programs and architecture. Algorithms documented in TOMS are available as the Collected Algorithms of the ACM at calgo.acm.org.
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