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Analysis of Parallel Preconditioned Conjugate Gradient Algorithms
Volume 16, Issue 3 (2005), pp. 317–332
Raimondas Čiegis  

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https://doi.org/10.15388/Informatica.2005.101
Pub. online: 1 January 2005      Type: Research Article     

Received
1 December 2004
Published
1 January 2005

Abstract

The conjugate gradient method is an iterative technique used to solve systems of linear equations. The paper analyzes the performance of parallel preconditioned conjugate gradient algorithms. First, a theoretical model is proposed for estimation of the complexity of PPCG method and a scalability analysis is done for three different data decomposition cases. Computational experiments are done on IBM SP4 computer and some results are presented. It is shown that theoretical predictions agree well with computational results.

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Keywords
parallel algorithms preconditioned conjugate gradient method scalability analysis incomplete factorization

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INFORMATICA

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