1 Ocak 2013 Dergi makalesi Açık Erişim

Ari, Ismail; Muhtaroglu, Nitel

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/15797</identifier>
  <creators>
    <creator>
      <creatorName>Ari, Ismail</creatorName>
      <givenName>Ismail</givenName>
      <familyName>Ari</familyName>
      <affiliation>Ozyegin Univ, Dept Comp Sci, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Muhtaroglu, Nitel</creatorName>
      <givenName>Nitel</givenName>
      <familyName>Muhtaroglu</familyName>
      <affiliation>Ozyegin Univ, Dept Comp Sci, Istanbul, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Design And Implementation Of A Cloud Computing Service For Finite Element Analysis</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2013</publicationYear>
  <dates>
    <date dateType="Issued">2013-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/15797</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1016/j.advengsoft.2012.10.003</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">This paper presents an end-to-end discussion on the technical issues related to the design and implementation of a new cloud computing service for finite element analysis (FEA). The focus is specifically on performance characterization of linear and nonlinear mechanical structural analysis workloads over multi-core and multi-node computing resources. We first analyze and observe that accurate job characterization, tuning of multi-threading parameters and effective multi-core/node scheduling are critical for service performance. We design a "smart" scheduler that can dynamically select some of the required parameters, partition the load and schedule it in a resource-aware manner. We can achieve up to 7.53 x performance improvement over an aggressive scheduler using mixed FEA loads. We also discuss critical issues related to the data privacy, security, accounting, and portability of the cloud service. (C) 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.</description>
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