A blocked QR-decomposition for the parallel symmetric eigenvalue problem

T. Auckenthaler, T. Huckle, R. Wittmann

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In this paper we present a new stable algorithm for the parallel QR-decomposition of "tall and skinny" matrices. The algorithm has been developed for the dense symmetric eigensolver ELPA, where the QR-decomposition of tall and skinny matrices represents an important substep. Our new approach is based on the fast but unstable CholeskyQR algorithm (Stathopoulos and Wu, 2002) [1]. We show the stability of our new algorithm and provide promising results of our MPI-based implementation on a BlueGene/P and a Power6 system.

Original languageEnglish
Pages (from-to)186-194
Number of pages9
JournalParallel Computing
Volume40
Issue number7
DOIs
StatePublished - Jul 2014

Keywords

  • Eigenvalue and eigenvector computation
  • Parallelization
  • QR-decomposition
  • Two-step tridiagonalization

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