July 1, 2019 Conference paper Open Access

Leon, Vasileios; Asimakopoulos, Konstantinos; Xydis, Sotirios; Soudris, Dimitrios; Pekmestzi, Kiamal

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  <identifier identifierType="URL">https://zenodo.org/record/3472504</identifier>
  <creators>
    <creator>
      <creatorName>Leon, Vasileios</creatorName>
      <givenName>Vasileios</givenName>
      <familyName>Leon</familyName>
      <affiliation>National Technical University of Athens, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Asimakopoulos, Konstantinos</creatorName>
      <givenName>Konstantinos</givenName>
      <familyName>Asimakopoulos</familyName>
      <affiliation>National Technical University of Athens, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Xydis, Sotirios</creatorName>
      <givenName>Sotirios</givenName>
      <familyName>Xydis</familyName>
      <affiliation>National Technical University of Athens, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Soudris, Dimitrios</creatorName>
      <givenName>Dimitrios</givenName>
      <familyName>Soudris</familyName>
      <affiliation>National Technical University of Athens, Greece</affiliation>
    </creator>
    <creator>
      <creatorName>Pekmestzi, Kiamal</creatorName>
      <givenName>Kiamal</givenName>
      <familyName>Pekmestzi</familyName>
      <affiliation>National Technical University of Athens, Greece</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Cooperative Arithmetic-Aware Approximation Techniques for Energy-Efficient Multipliers</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <dates>
    <date dateType="Issued">2019-07-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3472504</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1145/3316781.3317793</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://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;Approximate computing appears as an emerging and promising solution for energy-efficient system designs, exploiting the inherent error-tolerant nature of various applications. In this paper, targeting multiplication circuits, i.e., the energy-hungry counterpart of hardware accelerators, an extensive exploration of the error--energy trade-off, when combining arithmetic-level approximation techniques, is performed for the first time. Arithmetic-aware approximations deliver significant energy reductions, while allowing to control the error values with discipline by setting accordingly a configuration parameter. Inspired from the promising results of prior works with one configuration parameter, we propose 5 hybrid design families for approximate and energy-friendly hardware multipliers, consisting of two independent parameters to tune the approximation levels. Interestingly, the resolution of the state-of-the-art Pareto diagram is improved, giving the flexibility to achieve better energy gains for a specific error constraint imposed by the system. Moreover, we outperform prior works in the field of approximate multipliers by up to 60% energy reduction, and thus, we define the new Pareto front.&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/H2020/780572/">780572</awardNumber>
      <awardTitle>Software Development toolKit for Energy optimization and technical Debt elimination</awardTitle>
    </fundingReference>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/801015/">801015</awardNumber>
      <awardTitle>Enhancing Programmability and boosting Performance Portability for Exascale Computing Systems</awardTitle>
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