Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems

The decomposition algorithms provide approaches to deal with NP-hardness in solving discrete optimization problems (DOPs). In this article one of the promising ways to exploit sparse matrices - local elimination algorithm in parallel interpretation (LEAP) are demonstrated. That is a graph-based stru...

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Main Author: D. V. Lemtyuzhnikova
Format: Article
Language:Russian
Published: Institute of Computer Science 2015-06-01
Series:Компьютерные исследования и моделирование
Subjects:
Online Access:http://crm.ics.org.ru/uploads/crmissues/crm_2015_3/15743.pdf
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spelling doaj-a2b9e408fa1144ac8a4e036e1336c8082020-11-25T02:03:37ZrusInstitute of Computer ScienceКомпьютерные исследования и моделирование2076-76332077-68532015-06-017369970510.20537/2076-7633-2015-7-3-699-7052326Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problemsD. V. LemtyuzhnikovaThe decomposition algorithms provide approaches to deal with NP-hardness in solving discrete optimization problems (DOPs). In this article one of the promising ways to exploit sparse matrices - local elimination algorithm in parallel interpretation (LEAP) are demonstrated. That is a graph-based structural decomposition algorithm, which allows to compute a solution in stages such that each of them uses results from previous stages. At the same time LEAP heavily depends on elimination ordering which actually provides solving stages. Also paper considers tree- and block-parallel for LEAP and required realization process of it comparison of a several heuristics for obtaining a better elimination order and shows how is related graph structure, elimination ordering and solving time.http://crm.ics.org.ru/uploads/crmissues/crm_2015_3/15743.pdfdiscrete optimizationvolunteer computinglocal elimination algorithmparallel computingsparse problemselimination tree
collection DOAJ
language Russian
format Article
sources DOAJ
author D. V. Lemtyuzhnikova
spellingShingle D. V. Lemtyuzhnikova
Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
Компьютерные исследования и моделирование
discrete optimization
volunteer computing
local elimination algorithm
parallel computing
sparse problems
elimination tree
author_facet D. V. Lemtyuzhnikova
author_sort D. V. Lemtyuzhnikova
title Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
title_short Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
title_full Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
title_fullStr Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
title_full_unstemmed Parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
title_sort parallel representation of local elimination algorithm for accelerating the solving sparse discrete optimization problems
publisher Institute of Computer Science
series Компьютерные исследования и моделирование
issn 2076-7633
2077-6853
publishDate 2015-06-01
description The decomposition algorithms provide approaches to deal with NP-hardness in solving discrete optimization problems (DOPs). In this article one of the promising ways to exploit sparse matrices - local elimination algorithm in parallel interpretation (LEAP) are demonstrated. That is a graph-based structural decomposition algorithm, which allows to compute a solution in stages such that each of them uses results from previous stages. At the same time LEAP heavily depends on elimination ordering which actually provides solving stages. Also paper considers tree- and block-parallel for LEAP and required realization process of it comparison of a several heuristics for obtaining a better elimination order and shows how is related graph structure, elimination ordering and solving time.
topic discrete optimization
volunteer computing
local elimination algorithm
parallel computing
sparse problems
elimination tree
url http://crm.ics.org.ru/uploads/crmissues/crm_2015_3/15743.pdf
work_keys_str_mv AT dvlemtyuzhnikova parallelrepresentationoflocaleliminationalgorithmforacceleratingthesolvingsparsediscreteoptimizationproblems
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