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PSPIKE : A Parallel Hybrid Sparse Linear System Solver
Date
2008-08-28
Author
Manguoğlu, Murat
Schenk, Olaf
Metadata
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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.
Subject Keywords
Tridiagonal systems
,
Cyclic reduction
,
Graphics processing unit
,
Direct solvers
,
Hybrid solvers
,
Krylov subspace methods
,
Sparse linear systems
URI
https://hdl.handle.net/11511/74179
https://user.ceng.metu.edu.tr/~manguoglu/PDFs/1569183598.pdf
DOI
https://doi.org/10.1007/978-3-642-03869-3_74
Conference Name
15th International Euro-Par Conference (25-28 August 2009)
Collections
Department of Computer Engineering, Conference / Seminar
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M. Manguoğlu and O. Schenk, “PSPIKE : A Parallel Hybrid Sparse Linear System Solver,” Netherlands, 2008, vol. 5704, p. 797, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/74179.