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<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>doi:10.1016/j.jpdc.2018.10.010</dc:identifier><dc:language>eng</dc:language><dc:creator>Ferrerón, A.</dc:creator><dc:creator>Alastruey-Benedé, J.</dc:creator><dc:creator>Suárez Gracia, D.</dc:creator><dc:creator>Monreal Arnal, T.</dc:creator><dc:creator>Ibáñez Marín, P.</dc:creator><dc:creator>Viñals Yúfera, V.</dc:creator><dc:title>A fault-tolerant last level cache for CMPs operating at ultra-low voltage</dc:title><dc:identifier>ART-2019-109702</dc:identifier><dc:description>Voltage scaling to values near the threshold voltage is a promising technique to hold off the many-core power wall. However, as voltage decreases, some SRAM cells are unable to operate reliably and show a behavior consistent with a hard fault. Block disabling is a micro-architectural technique that allows low-voltage operation by deactivating faulty cache entries, at the expense of reducing the effective cache capacity. In the case of the last-level cache, this capacity reduction leads to an increase in off-chip memory accesses, diminishing the overall energy benefit of reducing the voltage supply. In this work, we exploit the reuse locality and the intrinsic redundancy of multi-level inclusive hierarchies to enhance the performance of block disabling with negligible cost. The proposed fault-aware last-level cache management policy maps critical blocks, those not present in private caches and with a higher probability of being reused, to active cache entries. Our evaluation shows that this fault-aware management results in up to 37.3% and 54.2% fewer misses per kilo instruction (MPKI) than block disabling for multiprogrammed and parallel workloads, respectively. This translates to performance enhancements of up to 13% and 34.6% for multiprogrammed and parallel workloads, respectively.</dc:description><dc:date>2019</dc:date><dc:source>http://zaguan.unizar.es/record/84684</dc:source><dc:doi>10.1016/j.jpdc.2018.10.010</dc:doi><dc:identifier>http://zaguan.unizar.es/record/84684</dc:identifier><dc:identifier>oai:zaguan.unizar.es:84684</dc:identifier><dc:relation>info:eu-repo/grantAgreement/ES/DGA/T58-17R</dc:relation><dc:relation>info:eu-repo/grantAgreement/ES/MINECO/TIN2015-65316-P</dc:relation><dc:relation>info:eu-repo/grantAgreement/ES/MINECO/TIN2016-76635-C2-1-R</dc:relation><dc:identifier.citation>JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 125 (2019), 31-44</dc:identifier.citation><dc:rights>All rights reserved</dc:rights><dc:rights>http://www.europeana.eu/rights/rr-f/</dc:rights><dc:rights>info:eu-repo/semantics/openAccess</dc:rights></dc:dc>

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