New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice

The Projected Aggregation Methods generate the new point xk+1 as the projection ofxk onto an "aggregate" hyperplane usually arising from linear combinations of the hyperplanes planes defined by the blocks. In [13] an acceleration scheme was introduced for algorithms in which an optimized s...

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Autores principales: Scolnik, H., Echebest, N., Guardarucci, M.T., Vacchino, M.C.
Formato: SER
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_1570579X_v8_nC_p457_Scolnik
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spelling todo:paper_1570579X_v8_nC_p457_Scolnik2023-10-03T16:26:49Z New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice Scolnik, H. Echebest, N. Guardarucci, M.T. Vacchino, M.C. parallel iterative methods projected aggregation methods row partition strategies The Projected Aggregation Methods generate the new point xk+1 as the projection ofxk onto an "aggregate" hyperplane usually arising from linear combinations of the hyperplanes planes defined by the blocks. In [13] an acceleration scheme was introduced for algorithms in which an optimized search direction arises from the solution of small quadratic subproblems. In this paper we extend that theory to classical methods like Cimmino's and to the generalized convex combination as defined in [5]. We prove that the resulting new highly parallel, algorithms improve the original convergence rate and present numerical results which show their outstanding computational efficiency. © 2001 Elsevier B.V. All rights reserved. SER info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_1570579X_v8_nC_p457_Scolnik
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic parallel iterative methods
projected aggregation methods
row partition strategies
spellingShingle parallel iterative methods
projected aggregation methods
row partition strategies
Scolnik, H.
Echebest, N.
Guardarucci, M.T.
Vacchino, M.C.
New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice
topic_facet parallel iterative methods
projected aggregation methods
row partition strategies
description The Projected Aggregation Methods generate the new point xk+1 as the projection ofxk onto an "aggregate" hyperplane usually arising from linear combinations of the hyperplanes planes defined by the blocks. In [13] an acceleration scheme was introduced for algorithms in which an optimized search direction arises from the solution of small quadratic subproblems. In this paper we extend that theory to classical methods like Cimmino's and to the generalized convex combination as defined in [5]. We prove that the resulting new highly parallel, algorithms improve the original convergence rate and present numerical results which show their outstanding computational efficiency. © 2001 Elsevier B.V. All rights reserved.
format SER
author Scolnik, H.
Echebest, N.
Guardarucci, M.T.
Vacchino, M.C.
author_facet Scolnik, H.
Echebest, N.
Guardarucci, M.T.
Vacchino, M.C.
author_sort Scolnik, H.
title New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice
title_short New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice
title_full New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice
title_fullStr New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice
title_full_unstemmed New optimized and accelerated pam methods for solving large non-symmetric linear systems: Theory and practice
title_sort new optimized and accelerated pam methods for solving large non-symmetric linear systems: theory and practice
url http://hdl.handle.net/20.500.12110/paper_1570579X_v8_nC_p457_Scolnik
work_keys_str_mv AT scolnikh newoptimizedandacceleratedpammethodsforsolvinglargenonsymmetriclinearsystemstheoryandpractice
AT echebestn newoptimizedandacceleratedpammethodsforsolvinglargenonsymmetriclinearsystemstheoryandpractice
AT guardaruccimt newoptimizedandacceleratedpammethodsforsolvinglargenonsymmetriclinearsystemstheoryandpractice
AT vacchinomc newoptimizedandacceleratedpammethodsforsolvinglargenonsymmetriclinearsystemstheoryandpractice
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