Conference paper Open Access

# Cooperative Arithmetic-Aware Approximation Techniques for Energy-Efficient Multipliers

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

### DataCite XML Export

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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>
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<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>
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<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3472504</alternateIdentifier>
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<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1145/3316781.3317793</relatedIdentifier>
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<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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<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>
</fundingReference>
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