Improvements to SLEPc in Releases 3.14–3.18

Jose E. Roman, Fernando Alvarruiz, Carmen Campos, Lisandro Dalcin, Pierre Jolivet, Alejandro Lamas Daviña

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish (US)
JournalACM Transactions on Mathematical Software
StatePublished - Jun 7 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-06-12
Acknowledgements: This work was partially funded by the Spanish Agencia Estatal de Investigación under grant PID2019-107379RBI00 / AEI / 10.13039/501100011033. In addition to the authors of this paper, the following people contributed code to the releases: Fande Kong, Barry Smith, Satish Balay, Matthew Knepley, Stefano Zampini, Jacob Faibussowitsch, Murat Keçeli, William Dawn, Marco Morandini, Alexei Colin, Jan Blechta, Jack Hale, Elisa Schenone. Their contributions are much appreciated!

ASJC Scopus subject areas

  • Software
  • Applied Mathematics


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