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
Bertaccini, D., Filippone, S. (2014). Approximate Inverse Preconditioners for Krylov Methods on Heterogeneous Parallel Computers. In A.B. M. Bader (a cura di), Parallel Computing: Accelerating Computational Science and Engineering (CSE). ADVANCES IN PARALLEL COMPUTING (pp. 183-192). IOS Press [10.3233/978-1-61499-381-0-183].
Approximate Inverse Preconditioners for Krylov Methods on Heterogeneous Parallel Computers
BERTACCINI, DANIELE;FILIPPONE, SALVATORE
2014-01-01
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| File | Dimensione | Formato | |
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