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GPU-Accelerated Preconditioned GMRES Solver

Authors: Bo Yang 0020; Hui Liu 0005; Zhangxin Chen; Xuhong Tian;

GPU-Accelerated Preconditioned GMRES Solver

Abstract

Linear solvers and parallel computing are crucial for developing a new generation reservoir simulator. To acquire satisfied acceleration performance, we study the parallel algorithms of linear solvers with preconditioners on GPUs (Graphics Processing Units). The classical GMRES solver is implemented, and the parallelization of ILU(0) and ILUT preconditioners based on the Restricted Additive Schwarz (RAS) method is studied. We also develop a parallel triangular solver to solve preconditioner systems on GPUs. The numerical experiments demonstrate our ILU preconditioned solver has favorable acceleration performance against a traditional CPU.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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