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On the performance of parallel approximate inverse preconditioning using Java multithreading techniques
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DOI：10.1016/j.amc.2007.01.024.png)
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Abstract
En 中文
In this paper a parallel shared memory Java multithreaded design and implementation of the explicit approximate inverse preconditioning is presented for solving efficiently arrow-typc linear systems on symmetric multiprocessor systems. A new parallel algorithm for computing a class of optimized approximate inverse matrix is introduced. The performance on a symmetric multiprocessor system, using Java multithreading, is investigated by solving characteristic arrow-type linear systems and numerical results are given, considering the parallel performance of the construction of the optimized approximate inverse and the explicit preconditioned generalized conjugate gradient square scheme. (C) 2007 Elsevier Inc. All rights reserved.
Keywords:
arrow-type matrix
parallel approximate inverse matrix algorithm
preconditioning
parallel conjugate gradient type methods
object oriented methodology
Java multithreading
symmetric multiprocessor systems
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
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