Title

Designing And Evaluating Redundancy-Based Soft-Error Masking On A Continuum Of Energy Versus Robustness

Keywords

Delay variation; design diversity; energy-efficient computing; fault resilience; near-threshold voltage (NTV); redundancy-based mitigation techniques; reliability; soft-error rate (SER)

Abstract

Near-threshold computing is an effective strategy to reduce the power dissipation of deeply-scaled CMOS logic circuits. However, near-threshold strategies exacerbate the impact of delay variations on device performance and increase the susceptibility to soft errors due to narrow voltage margins. The objective of this work is to develop and assess design approaches that leverage tradeoffs between performance and the resilience of fault masking coverage for various soft-error mitigation techniques. The primary insight from this work is identification of redundancy-based hardening techniques that can deliver increased benefits in terms of the fault coverage energy ratio (FCER) for the leveraged tradeoffs within iso-energy constraints at near-threshold voltage (NTV). Simulation results demonstrate that temporal redundancy approaches offer favorable tradeoffs in terms of FCER. They exhibit reduced impact on performance variations and achieve extensive soft fault masking, therefore improving the system robustness within acceptable delay constraints. Meanwhile, it is shown that a hybrid redundancy approach can be used to protect a low-power system to maintain throughput while tolerating soft errors. We demonstrate how the FCER metric can be used as an optimization parameter to guide circuit synthesis to meet performance and robustness goals. Finally, the impact of design diversity on spatial and hybrid redundancy at NTV is assessed in terms of FCER and delay variation to form overall recommendations regarding soft-error mitigation at NTV.

Publication Date

7-1-2018

Publication Title

IEEE Transactions on Sustainable Computing

Volume

3

Issue

3

Number of Pages

139-152

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/TSUSC.2017.2764857

Socpus ID

85081759492 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85081759492

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