Parallel performance of the coarse space linear vertex solver and low energy basis preconditioner for spectral/hp elements

被引:15
作者
Grinberg, L. [1 ]
Pekurovsky, D. [2 ]
Sherwin, S. J. [3 ]
Karniadakis, G. E. [1 ]
机构
[1] Brown Univ, Div Appl Math, Providence, RI 02912 USA
[2] Univ Calif San Diego, San Diego Supercomp Ctr, La Jolla, CA 92093 USA
[3] Imperial Coll Sci Technol & Med, Dept Aeronaut, London SW7 2BY, England
基金
美国国家科学基金会;
关键词
High-order accuracy; Petaflop computing; CFD; Arterial flows;
D O I
10.1016/j.parco.2008.12.002
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The big bottleneck in scaling PDE-based codes to petaflop computing is scalability of effective preconditioners. We have developed and implemented an effective and scalable low energy basis preconditioner (LEBP) for elliptic solvers, leading to computational savings of an order of magnitude with respect to other preconditioners. The efficiency of LEBP relies on the implementation of parallel matrix-vector multiplication required by coarse solver to handle the h-scaling. We provide details on optimization, parallel performance and implementation of the coarse grain solver and show scalability of LEBP on the IBM Blue Gene and the Cray XT3. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:284 / 304
页数:21
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