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dc.creatorKoutsovasilis P., Parasyris K., Antonopoulos C.D., Bellas N., Lalis S.en
dc.date.accessioned2023-01-31T08:46:31Z
dc.date.available2023-01-31T08:46:31Z
dc.date.issued2020
dc.identifier10.1109/TPDS.2020.3004383
dc.identifier.issn10459219
dc.identifier.urihttp://hdl.handle.net/11615/75445
dc.description.abstractChip manufacturers introduce redundancy at various levels of CPU design to guarantee correct operation, even for worst-case combinations of non-idealities in process variation and system operating conditions. This redundancy is implemented partly in the form of voltage margins. However, for a wide range of real-world execution scenarios these margins are excessive and merely translate to increased power consumption, hindering the effort towards higher energy efficiency in both HPC and general purpose computing. Our study on the x86-64 Haswell and Skylake multicore microarchitectures reveals wide voltage margins, which vary across different microarchitectures, different chip parts of the same microarchitecture, and across different workloads. We find that it is necessary to quantify voltage margins using multi-threaded and multi-instance workloads, as characterization with single-threaded and single-instance workloads that do not stress the CPU to its full capacity typically identifies overly optimistic margins that lead to errors when applied in realistic program execution scenarios. In addition, we introduce, deploy and evaluate a run-time governor that dynamically reduces the supply voltage of modern multicore x86-64 CPUs. Our governor employs a model that takes as input a set of performance metrics which are directly measurable via performance monitoring counters and have high predictive value for the minimum tolerable supply voltage ($V_{min}$Vmin), to predict and apply the appropriate reduction for the workload at hand. Compared with the conventional DVFS governor, our approach achieves up to 42 percent energy savings for the Skylake family and 34 percent for the Haswell family for complex, real-world applications. © 1990-2012 IEEE.en
dc.language.isoenen
dc.sourceIEEE Transactions on Parallel and Distributed Systemsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85088584442&doi=10.1109%2fTPDS.2020.3004383&partnerID=40&md5=946513304a66c2e2f7dd640282d83a84
dc.subjectComputer architectureen
dc.subjectGovernorsen
dc.subjectGreen computingen
dc.subjectProgram processorsen
dc.subjectRedundancyen
dc.subjectChip manufacturersen
dc.subjectExecution scenarioen
dc.subjectGeneral-purpose computingen
dc.subjectMicro architecturesen
dc.subjectOperating conditionen
dc.subjectPerformance metricsen
dc.subjectPerformance monitoringen
dc.subjectPredictive valuesen
dc.subjectEnergy efficiencyen
dc.subjectIEEE Computer Societyen
dc.titleDynamic Undervolting to Improve Energy Efficiency on Multicore X86 CPUsen
dc.typejournalArticleen


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