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Approximate Inverse Preconditioners for Krylov Methods on Heterogeneous Parallel Computers
Daniele Bertaccini, Salvatore Filippone
183 - 192
10.3233/978-1-61499-381-0-183
Advances in Parallel Computing
Volume 25: Parallel Computing: Accelerating Computational Science and Engineering (CSE)
Abstract

The popularity of GPGPUs in high performance platforms for scientific computing in recent times has renewed interest in approximate inverse preconditioners for Krylov methods. We have recently introduced some new algorithmic variants [6] of popular approximate inverse methods. We now report on the behaviour of these variations in high performance multilevel preconditioning frameworks, and we present the software framework that enables us to easily deal with heterogeneous computing platforms that include GPGPUs.

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