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PSPIKE: A Parallel Hybrid Sparse Linear System Solver

Manguoglu, Murat and Sameh, Ahmed and O. Schenk, Olaf. (2009) PSPIKE: A Parallel Hybrid Sparse Linear System Solver. In: Euro-Par 2009 Parallel Processing : 15th International Euro-Par Conference, Delft, The Netherlands, August 25-28, 2009. Proceedings. Berlin, S. 797-808.

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Official URL: http://edoc.unibas.ch/dok/A5254970

Abstract

The availability of large-scale computing platforms comprised of tens of thousands of multicore processors motivates the need for the next generation of highly scalable sparse linear system solvers. These solvers must optimize parallel performance, processor (serial) performance, as well as memory requirements, while being robust across broad classes of applications and systems. In this paper, we present a new parallel solver that combines the desirable characteristics of direct methods (robustness) and effective iterative solvers (low computational cost), while alleviating their drawbacks (memory requirements, lack of robustness). Our proposed hybrid solver is based on the general sparse solver PARDISO, and the “Spike” family of hybrid solvers. The resulting algorithm, called PSPIKE, is as robust as direct solvers, more reliable than classical preconditioned Krylov subspace methods, and much more scalable than direct sparse solvers. We support our performance and parallel scalability claims using detailed experimental studies and comparison with direct solvers, as well as classical preconditioned Krylov methods.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik
Item Type:Conference or Workshop Item, refereed
Bibsysno:Link to catalogue
Publisher:Springer
ISBN:978-3-642-03869-3 ; 978-3-642-03868-6
Series Name:Lecture Notes in Computer Science
Issue Number:5704
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:22 Mar 2012 14:25
Deposited On:22 Mar 2012 13:48

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