BandiTS: Dynamic timing speculation using multi-armed bandit based optimization

Jeff Jun Zhang, Siddharth Garg

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

Abstract

Timing speculation has recently been proposed as a method for increasing performance beyond that achievable by conventional worst-case design techniques. Starting with the observation of fast temporal variations in timing error probabilities, we propose a run-time technique to dynamically determine the optimal degree of timing speculation (i.e., how aggressively the processor is over-clocked) based on a novel formulation of the dynamic timing speculation problem as a multi-armed bandit problem. By conducting detailed post-synthesis timing simulations on a 5-stage MIPS processor running a variety of workloads, the proposed adaptive mechanism improves processor's performance significantly comparing with a competing approach (about 8.3% improvement); on the other hand, it shows only about 2.8% performance loss on average, compared with the oracle results.

Original languageEnglish (US)
Title of host publicationProceedings of the 2017 Design, Automation and Test in Europe, DATE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages922-925
Number of pages4
ISBN (Electronic)9783981537093
DOIs
StatePublished - May 11 2017
Event20th Design, Automation and Test in Europe, DATE 2017 - Swisstech, Lausanne, Switzerland
Duration: Mar 27 2017Mar 31 2017

Publication series

NameProceedings of the 2017 Design, Automation and Test in Europe, DATE 2017

Other

Other20th Design, Automation and Test in Europe, DATE 2017
Country/TerritorySwitzerland
CitySwisstech, Lausanne
Period3/27/173/31/17

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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