Using the parallel algebraic recursive multilevel solver in modern physical applications

M. Sosonkina, Yousef Saad, X. Cai

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


This paper discusses the application of a few parallel preconditioning techniques, which are collected in a recently developed suite of codes Parallel Algebraic Recursive Multilevel Solver (pARMS), to tackling large-scale sparse linear systems arising from real-life applications. In particular, we study the effect of different algorithmic variations and parameter choices on the overall performance of the distributed preconditioners in pARMS by means of numerical experiments related to a few realistic applications. These applications include magnetohydrodynamics, nonlinear acoustic field simulation, and tire design.

Original languageEnglish (US)
Pages (from-to)489-500
Number of pages12
JournalFuture Generation Computer Systems
Issue number3
StatePublished - Apr 1 2004

Bibliographical note

Funding Information:
This work was supported in part by NSF under grants NSF/ACI-0000443 and NSF/INT-0003274, and in part by the Minnesota Supercomputing Institute.


  • Distributed sparse linear systems
  • Magnetohydrodynamic flows
  • Nonlinear acoustic field simulation
  • Parallel algebraic multilevel preconditioning
  • Tire design


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