Conference paper Open Access

Learning-based Dynamic Pinning of Parallelized Applications in Many-Core Systems

Chasparis, Georgios; Janjic, Vladimir; Rossbory, Michael; Hammond, Kevin


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  <identifier identifierType="DOI">10.5281/zenodo.1186660</identifier>
  <creators>
    <creator>
      <creatorName>Chasparis, Georgios</creatorName>
      <givenName>Georgios</givenName>
      <familyName>Chasparis</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3059-3575</nameIdentifier>
      <affiliation>Software Competence Center Hagenberg GmbH</affiliation>
    </creator>
    <creator>
      <creatorName>Janjic, Vladimir</creatorName>
      <givenName>Vladimir</givenName>
      <familyName>Janjic</familyName>
      <affiliation>University of St Andrews</affiliation>
    </creator>
    <creator>
      <creatorName>Rossbory, Michael</creatorName>
      <givenName>Michael</givenName>
      <familyName>Rossbory</familyName>
      <affiliation>Software Competence Center Hagenberg GmbH</affiliation>
    </creator>
    <creator>
      <creatorName>Hammond, Kevin</creatorName>
      <givenName>Kevin</givenName>
      <familyName>Hammond</familyName>
      <affiliation>University of St Andrews</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Learning-based Dynamic Pinning of Parallelized Applications in Many-Core Systems</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2018</publicationYear>
  <dates>
    <date dateType="Issued">2018-03-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1186660</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1186659</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This paper introduces a reinforcement-learning based resource allocation framework for dynamic placement of threads of parallel applications to Non-Uniform Memory Access (NUMA) many-core systems. We propose a two-level learning-based decision making process, where at the first level each thread independently decides on which group of cores (NUMA node) it will execute, and on the second level it decides to which particular core from the group it will be pinned. Additionally, a novel performance-based learning dynamics is introduced to handle measurement noise and rapid variations in the performance of the threads. Experiments on a 24-core system show the improvement of up to 16% in the execution time of parallel applications under our framework, compared to the Linux operating system scheduler.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/644235/">644235</awardNumber>
      <awardTitle>REfactoring Parallel Heterogeneous Resource-Aware Applications  - a Software Engineering Approach</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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