LU factorization using multithreaded system

The problem of solving large systems of linear equations of the form (Ax = b) arises in various applications such as finite element analysis, computational fluid dynamics, and power systems analysis, which is of high algorithms complexities, that takes a lot of execution time. The high computational...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Badawy, M. O., Hanafy, Y. Y., Eltarras, R.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 14
container_issue
container_start_page 9
container_title
container_volume
creator Badawy, M. O.
Hanafy, Y. Y.
Eltarras, R.
description The problem of solving large systems of linear equations of the form (Ax = b) arises in various applications such as finite element analysis, computational fluid dynamics, and power systems analysis, which is of high algorithms complexities, that takes a lot of execution time. The high computational power required for fast solution of such problem is beyond the reach of present day conventional uniprocessor. Furthermore, the performance of using a system of uniprocessor tends to display an early saturation in relation to their costs. This implies that even modest gains in performance of a uniprocessor come at an exorbitant increase in its cost, that made the use of new technologies mandatory to minimize the execution time. This paper presents a parallel implementation of the classical solution of system of linear equations at high and reasonable speed up. The speed up achievement is obtained through the fine granularity in data and tasks, and asynchronicity to hide latency of memory access.
doi_str_mv 10.1109/ICCTA.2012.6523540
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6523540</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6523540</ieee_id><sourcerecordid>6523540</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-4dbe164940bc0030d6f1ee05413f2fef3ac0c7633ea30c0a20fbc2e4d8f828703</originalsourceid><addsrcrecordid>eNpFj81KAzEURiNSUGtfQDezlxlvcvPXZRm0FgbctOuSSW5qpNPKJF3Up1ew4OrjLM6Bj7EHDg3nMH9ete160QjgotFKoJJwxe641AaFFRKv_wHVDZvl_AkAv6Y21tyyp25TRefLcUzfrqTjoTrldNhVw2lfUvkYyQUKVT7nQsM9m0S3zzS77JRtXl_W7VvdvS9X7aKrEzeq1DL0xLWcS-g9AELQkROBkhyjiBTRefBGI5JD8OAExN4LksFGK6wBnLLHv24iou3XmAY3nreXc_gDxUpCyQ</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>LU factorization using multithreaded system</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Badawy, M. O. ; Hanafy, Y. Y. ; Eltarras, R.</creator><creatorcontrib>Badawy, M. O. ; Hanafy, Y. Y. ; Eltarras, R.</creatorcontrib><description>The problem of solving large systems of linear equations of the form (Ax = b) arises in various applications such as finite element analysis, computational fluid dynamics, and power systems analysis, which is of high algorithms complexities, that takes a lot of execution time. The high computational power required for fast solution of such problem is beyond the reach of present day conventional uniprocessor. Furthermore, the performance of using a system of uniprocessor tends to display an early saturation in relation to their costs. This implies that even modest gains in performance of a uniprocessor come at an exorbitant increase in its cost, that made the use of new technologies mandatory to minimize the execution time. This paper presents a parallel implementation of the classical solution of system of linear equations at high and reasonable speed up. The speed up achievement is obtained through the fine granularity in data and tasks, and asynchronicity to hide latency of memory access.</description><identifier>ISBN: 1467328235</identifier><identifier>ISBN: 9781467328234</identifier><identifier>EISBN: 1467328243</identifier><identifier>EISBN: 9781467328227</identifier><identifier>EISBN: 9781467328241</identifier><identifier>EISBN: 1467328227</identifier><identifier>DOI: 10.1109/ICCTA.2012.6523540</identifier><language>eng</language><publisher>IEEE</publisher><subject>Dense linear algebra ; LU factorization ; Many-core ; Multicore ; Multithreading ; Task scheduling</subject><ispartof>2012 22nd International Conference on Computer Theory and Applications (ICCTA), 2012, p.9-14</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6523540$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6523540$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Badawy, M. O.</creatorcontrib><creatorcontrib>Hanafy, Y. Y.</creatorcontrib><creatorcontrib>Eltarras, R.</creatorcontrib><title>LU factorization using multithreaded system</title><title>2012 22nd International Conference on Computer Theory and Applications (ICCTA)</title><addtitle>ICCTA</addtitle><description>The problem of solving large systems of linear equations of the form (Ax = b) arises in various applications such as finite element analysis, computational fluid dynamics, and power systems analysis, which is of high algorithms complexities, that takes a lot of execution time. The high computational power required for fast solution of such problem is beyond the reach of present day conventional uniprocessor. Furthermore, the performance of using a system of uniprocessor tends to display an early saturation in relation to their costs. This implies that even modest gains in performance of a uniprocessor come at an exorbitant increase in its cost, that made the use of new technologies mandatory to minimize the execution time. This paper presents a parallel implementation of the classical solution of system of linear equations at high and reasonable speed up. The speed up achievement is obtained through the fine granularity in data and tasks, and asynchronicity to hide latency of memory access.</description><subject>Dense linear algebra</subject><subject>LU factorization</subject><subject>Many-core</subject><subject>Multicore</subject><subject>Multithreading</subject><subject>Task scheduling</subject><isbn>1467328235</isbn><isbn>9781467328234</isbn><isbn>1467328243</isbn><isbn>9781467328227</isbn><isbn>9781467328241</isbn><isbn>1467328227</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFj81KAzEURiNSUGtfQDezlxlvcvPXZRm0FgbctOuSSW5qpNPKJF3Up1ew4OrjLM6Bj7EHDg3nMH9ete160QjgotFKoJJwxe641AaFFRKv_wHVDZvl_AkAv6Y21tyyp25TRefLcUzfrqTjoTrldNhVw2lfUvkYyQUKVT7nQsM9m0S3zzS77JRtXl_W7VvdvS9X7aKrEzeq1DL0xLWcS-g9AELQkROBkhyjiBTRefBGI5JD8OAExN4LksFGK6wBnLLHv24iou3XmAY3nreXc_gDxUpCyQ</recordid><startdate>201210</startdate><enddate>201210</enddate><creator>Badawy, M. O.</creator><creator>Hanafy, Y. Y.</creator><creator>Eltarras, R.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201210</creationdate><title>LU factorization using multithreaded system</title><author>Badawy, M. O. ; Hanafy, Y. Y. ; Eltarras, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-4dbe164940bc0030d6f1ee05413f2fef3ac0c7633ea30c0a20fbc2e4d8f828703</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Dense linear algebra</topic><topic>LU factorization</topic><topic>Many-core</topic><topic>Multicore</topic><topic>Multithreading</topic><topic>Task scheduling</topic><toplevel>online_resources</toplevel><creatorcontrib>Badawy, M. O.</creatorcontrib><creatorcontrib>Hanafy, Y. Y.</creatorcontrib><creatorcontrib>Eltarras, R.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Badawy, M. O.</au><au>Hanafy, Y. Y.</au><au>Eltarras, R.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>LU factorization using multithreaded system</atitle><btitle>2012 22nd International Conference on Computer Theory and Applications (ICCTA)</btitle><stitle>ICCTA</stitle><date>2012-10</date><risdate>2012</risdate><spage>9</spage><epage>14</epage><pages>9-14</pages><isbn>1467328235</isbn><isbn>9781467328234</isbn><eisbn>1467328243</eisbn><eisbn>9781467328227</eisbn><eisbn>9781467328241</eisbn><eisbn>1467328227</eisbn><abstract>The problem of solving large systems of linear equations of the form (Ax = b) arises in various applications such as finite element analysis, computational fluid dynamics, and power systems analysis, which is of high algorithms complexities, that takes a lot of execution time. The high computational power required for fast solution of such problem is beyond the reach of present day conventional uniprocessor. Furthermore, the performance of using a system of uniprocessor tends to display an early saturation in relation to their costs. This implies that even modest gains in performance of a uniprocessor come at an exorbitant increase in its cost, that made the use of new technologies mandatory to minimize the execution time. This paper presents a parallel implementation of the classical solution of system of linear equations at high and reasonable speed up. The speed up achievement is obtained through the fine granularity in data and tasks, and asynchronicity to hide latency of memory access.</abstract><pub>IEEE</pub><doi>10.1109/ICCTA.2012.6523540</doi><tpages>6</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 1467328235
ispartof 2012 22nd International Conference on Computer Theory and Applications (ICCTA), 2012, p.9-14
issn
language eng
recordid cdi_ieee_primary_6523540
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Dense linear algebra
LU factorization
Many-core
Multicore
Multithreading
Task scheduling
title LU factorization using multithreaded system
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T10%3A48%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=LU%20factorization%20using%20multithreaded%20system&rft.btitle=2012%2022nd%20International%20Conference%20on%20Computer%20Theory%20and%20Applications%20(ICCTA)&rft.au=Badawy,%20M.%20O.&rft.date=2012-10&rft.spage=9&rft.epage=14&rft.pages=9-14&rft.isbn=1467328235&rft.isbn_list=9781467328234&rft_id=info:doi/10.1109/ICCTA.2012.6523540&rft_dat=%3Cieee_6IE%3E6523540%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1467328243&rft.eisbn_list=9781467328227&rft.eisbn_list=9781467328241&rft.eisbn_list=1467328227&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6523540&rfr_iscdi=true