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CE-Based Optimization for Real-time System Availability under Learned Soft Error Rate

  • Liying Li
  • , Tongquan Wei*
  • , Junlong Zhou
  • , Mingsong Chen
  • , Xiaobo Sharon Hu
  • *Corresponding author for this work
  • East China Normal University
  • Nanjing University of Science and Technology
  • University of Notre Dame

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As the density of integrated circuits continues to increase, the possibility that real-time systems suffer from transient and permanent failures rises significantly, resulting in a degraded availability of system functionality. In this paper, we investigate the dynamic modeling of transient failure rate based on Back Propagation (BP) neural network, and propose an optimization strategy for system availability based on Cross Entropy (CE). Specifically, the neural network is trained using cross-layer simulation data obtained from SPICE simulation while the CE-based optimization for system functionality availability is achieved by judiciously selecting an optimal supply voltage for processors under timing constraints. Simulation results show that the proposed method can achieve system availability improvement of up to 32% compared to benchmarking methods.

Original languageEnglish
Title of host publicationProceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1331-1336
Number of pages6
ISBN (Electronic)9783981926323
DOIs
StatePublished - 14 May 2019
Event22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019 - Florence, Italy
Duration: 25 Mar 201929 Mar 2019

Publication series

NameProceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019

Conference

Conference22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019
Country/TerritoryItaly
CityFlorence
Period25/03/1929/03/19

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