Parallelization of Implementations of Purely Sequential Algorithms
The work is dedicated to the parallelization of programs in especially difficult cases when the used algorithm is purely sequential, there are no parallel alternatives to this algorithm, and its execution time is unacceptably high. Various parallelization methods for software implementations of such...
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Veröffentlicht in: | Programming and computer software 2019-12, Vol.45 (7), p.381-389 |
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description | The work is dedicated to the parallelization of programs in especially difficult cases when the used algorithm is purely sequential, there are no parallel alternatives to this algorithm, and its execution time is unacceptably high. Various parallelization methods for software implementations of such algorithms and resulting computational load balancing are considered that make it possible to considerably accelerate the execution of application programs using purely sequential algorithms. The proposed methods are illustrated with examples of their application to two algorithms used in a dynamic binary code analysis toolset. The main goal of this paper is to show that the use of a purely sequential algorithm in a software implementation does not necessarily imply that its execution is inevitably sequential. The proposed methods of parallelizing implementations of such algorithms and balancing the resulting computational load can help develop efficient parallel programs that fully utilize the hardware capabilities of modern computers. |
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B. ; Kim, E. S. ; Solovev, M. A.</creator><creatorcontrib>Bugerya, A. B. ; Kim, E. S. ; Solovev, M. A.</creatorcontrib><description>The work is dedicated to the parallelization of programs in especially difficult cases when the used algorithm is purely sequential, there are no parallel alternatives to this algorithm, and its execution time is unacceptably high. Various parallelization methods for software implementations of such algorithms and resulting computational load balancing are considered that make it possible to considerably accelerate the execution of application programs using purely sequential algorithms. The proposed methods are illustrated with examples of their application to two algorithms used in a dynamic binary code analysis toolset. The main goal of this paper is to show that the use of a purely sequential algorithm in a software implementation does not necessarily imply that its execution is inevitably sequential. The proposed methods of parallelizing implementations of such algorithms and balancing the resulting computational load can help develop efficient parallel programs that fully utilize the hardware capabilities of modern computers.</description><identifier>ISSN: 0361-7688</identifier><identifier>EISSN: 1608-3261</identifier><identifier>DOI: 10.1134/S0361768819070053</identifier><language>eng</language><publisher>Moscow: Pleiades Publishing</publisher><subject>Algorithms ; Artificial Intelligence ; Binary codes ; Computer Science ; Computers ; Decomposition ; Operating Systems ; Parallel programming ; Software ; Software Engineering ; Software Engineering/Programming and Operating Systems</subject><ispartof>Programming and computer software, 2019-12, Vol.45 (7), p.381-389</ispartof><rights>Pleiades Publishing, Ltd. 2019</rights><rights>Pleiades Publishing, Ltd. 2019.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-80396dbaf8de0bb0ffd002f9ffd1179ca9c6e3eb92e58bece091285bbffda2813</citedby><cites>FETCH-LOGICAL-c316t-80396dbaf8de0bb0ffd002f9ffd1179ca9c6e3eb92e58bece091285bbffda2813</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1134/S0361768819070053$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918579998?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21367,27901,27902,33721,41464,42533,43781,51294</link.rule.ids></links><search><creatorcontrib>Bugerya, A. 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The proposed methods of parallelizing implementations of such algorithms and balancing the resulting computational load can help develop efficient parallel programs that fully utilize the hardware capabilities of modern computers.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Binary codes</subject><subject>Computer Science</subject><subject>Computers</subject><subject>Decomposition</subject><subject>Operating Systems</subject><subject>Parallel programming</subject><subject>Software</subject><subject>Software Engineering</subject><subject>Software Engineering/Programming and Operating Systems</subject><issn>0361-7688</issn><issn>1608-3261</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1UE1Lw0AQXUTBWv0B3gKeozO7TbJ7rMWPQsFC9Rx209masknqbnqov96NFTyIpwfva4bH2DXCLaKY3K1A5FjkUqKCAiATJ2yEOchU8BxP2WiQ00E_ZxchbAEQYDIZsful9to5cvWn7uuuTTqbzJudo4ba_psJA7Xce3KHZEUf-8jX2iVTt-l83b834ZKdWe0CXf3gmL09PrzOntPFy9N8Nl2klcC8TyUIla-NtnJNYAxYuwbgVkVELFSlVZWTIKM4ZdJQRaCQy8yYaNBcohizm2PvznfxjdCX227v23iy5AplViilZHTh0VX5LgRPttz5utH-UCKUw1Tln6lihh8zIXrbDfnf5v9DX1JbbDA</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Bugerya, A. 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subjects | Algorithms Artificial Intelligence Binary codes Computer Science Computers Decomposition Operating Systems Parallel programming Software Software Engineering Software Engineering/Programming and Operating Systems |
title | Parallelization of Implementations of Purely Sequential Algorithms |
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