Conference paper Open Access
Leon, Vasileios; Asimakopoulos, Konstantinos; Xydis, Sotirios; Soudris, Dimitrios; Pekmestzi, Kiamal
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="942" ind1=" " ind2=" "> <subfield code="a">2020-01-01</subfield> </datafield> <controlfield tag="005">20200120164914.0</controlfield> <controlfield tag="001">3472504</controlfield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">National Technical University of Athens, Greece</subfield> <subfield code="a">Asimakopoulos, Konstantinos</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">National Technical University of Athens, Greece</subfield> <subfield code="a">Xydis, Sotirios</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">National Technical University of Athens, Greece</subfield> <subfield code="a">Soudris, Dimitrios</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">National Technical University of Athens, Greece</subfield> <subfield code="a">Pekmestzi, Kiamal</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">225005</subfield> <subfield code="z">md5:600061dcbbe96fcc3ffcada2124c1856</subfield> <subfield code="u">https://zenodo.org/record/3472504/files/dac-Leon.pdf</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2019-07-01</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">openaire</subfield> <subfield code="o">oai:zenodo.org:3472504</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="u">National Technical University of Athens, Greece</subfield> <subfield code="a">Leon, Vasileios</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Cooperative Arithmetic-Aware Approximation Techniques for Energy-Efficient Multipliers</subfield> </datafield> <datafield tag="536" ind1=" " ind2=" "> <subfield code="c">780572</subfield> <subfield code="a">Software Development toolKit for Energy optimization and technical Debt elimination</subfield> </datafield> <datafield tag="536" ind1=" " ind2=" "> <subfield code="c">801015</subfield> <subfield code="a">Enhancing Programmability and boosting Performance Portability for Exascale Computing Systems</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield> <subfield code="a">Creative Commons Attribution 4.0 International</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><p>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.</p></subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.1145/3316781.3317793</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">conferencepaper</subfield> </datafield> </record>
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