Determining application-specific peak power and energy requirements for ultra-low power processors

Hari Cherupalli, Henry Duwe, Weidong Ye, Rakesh Kumar, John M Sartori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Many emerging applications such as IoT, wearables, implantables, and sensor networks are power- and energyconstrained. These applications rely on ultra-low-power processors that have rapidly become the most abundant type of processor manufactured today. In the ultra-low-power embedded systems used by these applications, peak power and energy requirements are the primary factors that determine critical system characteristics, such as size, weight, cost, and lifetime. While the power and energy requirements of these systems tend to be application-specific, conventional techniques for rating peak power and energy cannot accurately bound the power and energy requirements of an application running on a processor, leading to over-provisioning that increases system size and weight. In this paper, we present an automated technique that performs hardware-software coanalysis of the application and ultra-low-power processor in an embedded system to determine application-specific peak power and energy requirements. Our technique provides more accurate, tighter bounds than conventional techniques for determining peak power and energy requirements, reporting 15% lower peak power and 17% lower peak energy, on average, than a conventional approach based on profiling and guardbanding. Compared to an aggressive stressmarkbased approach, our technique reports power and energy bounds that are 26% and 26% lower, respectively, on average. Also, unlike conventional approaches, our technique reports guaranteed bounds on peak power and energy independent of an application's input set. Tighter bounds on peak power and energy can be exploited to reduce system size, weight, and cost.

Original languageEnglish (US)
Title of host publicationASPLOS 2017 - 22nd International Conference on Architectural Support for Programming Languages and Operating Systems
PublisherAssociation for Computing Machinery
Pages3-16
Number of pages14
ISBN (Electronic)9781450344654
DOIs
StatePublished - Apr 4 2017
Event22nd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2017 - Xi'an, China
Duration: Apr 8 2017Apr 12 2017

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
VolumePart F127193

Other

Other22nd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2017
CountryChina
CityXi'an
Period4/8/174/12/17

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Cherupalli, H., Duwe, H., Ye, W., Kumar, R., & Sartori, J. M. (2017). Determining application-specific peak power and energy requirements for ultra-low power processors. In ASPLOS 2017 - 22nd International Conference on Architectural Support for Programming Languages and Operating Systems (pp. 3-16). (International Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS; Vol. Part F127193). Association for Computing Machinery. https://doi.org/10.1145/3037697.3037711