Parallel variational iterative linear solvers
In this work we consider parallel variational algorithms for solution of linear systems. Theoretical analysis explains the superlinear convergence rate for two step gradient descent method. A new modification of the algorithm is proposed. Results of computational experiments are given for a lin...
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Vilnius Gediminas Technical University
2007-03-01
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doaj-b8e9664d4b6d4160abedf4336cd934fa2021-07-02T16:49:24ZengVilnius Gediminas Technical UniversityMathematical Modelling and Analysis1392-62921648-35102007-03-0112110.3846/1392-6292.2007.12.1-16Parallel variational iterative linear solversRaimondas Čiegis0Remigijus Čiegis1Alexander Jakušev2Gailė Šaltenienė3Vilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, LithuaniaVilnius Unicersity, Kaunas Faculty of Humanities, Mintės st. 8, LT-44280, Kaunas, LithuaniaVilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, LithuaniaVilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223 Vilnius, Lithuania In this work we consider parallel variational algorithms for solution of linear systems. Theoretical analysis explains the superlinear convergence rate for two step gradient descent method. A new modification of the algorithm is proposed. Results of computational experiments are given for a linear system of equations approximating 3D elliptic boundary value problem. All algorithms are implemented using parallel array object tool ParSol, then a parallel algorithm follows semi‐automatically from the serial one. Results of the scalability analysis are presented and the efficiency of the presented parallel algorithm is investigated experimentally. First Published Online: 14 Oct 2010 https://journals.vgtu.lt/index.php/MMA/article/view/7088variational iterative methodsparallel algorithmslinear algebra problemssoftware tools |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Raimondas Čiegis Remigijus Čiegis Alexander Jakušev Gailė Šaltenienė |
spellingShingle |
Raimondas Čiegis Remigijus Čiegis Alexander Jakušev Gailė Šaltenienė Parallel variational iterative linear solvers Mathematical Modelling and Analysis variational iterative methods parallel algorithms linear algebra problems software tools |
author_facet |
Raimondas Čiegis Remigijus Čiegis Alexander Jakušev Gailė Šaltenienė |
author_sort |
Raimondas Čiegis |
title |
Parallel variational iterative linear solvers |
title_short |
Parallel variational iterative linear solvers |
title_full |
Parallel variational iterative linear solvers |
title_fullStr |
Parallel variational iterative linear solvers |
title_full_unstemmed |
Parallel variational iterative linear solvers |
title_sort |
parallel variational iterative linear solvers |
publisher |
Vilnius Gediminas Technical University |
series |
Mathematical Modelling and Analysis |
issn |
1392-6292 1648-3510 |
publishDate |
2007-03-01 |
description |
In this work we consider parallel variational algorithms for solution of linear systems. Theoretical analysis explains the superlinear convergence rate for two step gradient descent method. A new modification of the algorithm is proposed. Results of computational experiments are given for a linear system of equations approximating 3D elliptic boundary value problem. All algorithms are implemented using parallel array object tool ParSol, then a parallel algorithm follows semi‐automatically from the serial one. Results of the scalability analysis are presented and the efficiency of the presented parallel algorithm is investigated experimentally.
First Published Online: 14 Oct 2010
|
topic |
variational iterative methods parallel algorithms linear algebra problems software tools |
url |
https://journals.vgtu.lt/index.php/MMA/article/view/7088 |
work_keys_str_mv |
AT raimondasciegis parallelvariationaliterativelinearsolvers AT remigijusciegis parallelvariationaliterativelinearsolvers AT alexanderjakusev parallelvariationaliterativelinearsolvers AT gailesalteniene parallelvariationaliterativelinearsolvers |
_version_ |
1721326165349629952 |