Minimizing synchronizations in sparse iterative solvers for distributed supercomputers

Sheng-Xin Zhu, Tong-Xiang Gu, Xing-Ping Liu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Eliminating synchronizations is one of the important techniques related to minimizing communications for modern high performance computing. This paper discusses principles of reducing communications due to global synchronizations in sparse iterative solvers on distributed supercomputers. We demonstrate how to minimize global synchronizations by rescheduling a typical Krylov subspace method. The benefit of minimizing synchronizations is shown in theoretical analysis and verified by numerical experiments. The experiments also show the local communications for some structured sparse matrix-vector multiplications and global communications in the underlying supercomputers increase in the order P1/2.5 and P4/5 respectively, where P is the number of processors. © 2013 Elsevier Ltd. All rights reserved.
Original languageEnglish (US)
Pages (from-to)199-209
Number of pages11
JournalComputers & Mathematics with Applications
Volume67
Issue number1
DOIs
StatePublished - Jan 2014
Externally publishedYes

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

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