Rowlings, Matthew orcid.org/0000-0003-3800-2055, Tyrrell, Andy orcid.org/0000-0002-8533-2404 and Trefzer, Martin Albrecht orcid.org/0000-0002-6196-6832 (2021) Operating Beyond FPGA Tool Limitations:Nervous Systems for Embedded Runtime Management. In: DATE '21:Proceedings of the 24th Conference on Design, Automation and Test in Europe. Design Automation and Test Europe, 01-05 Feb 2021 IEEE
Abstract
Fabrication issues throttle VLSI designs with pes- simistic design constraints and speed-grade device binning nec- essary to avoid failure of devices. We propose that a on chip monitoring system (a Nervous System) can reduce this margin by automatically sensing and reacting to failures and environmental changes at runtime. We demonstrate that pessimistic margins in the FPGA tools allow our test circuit to be overclocked by twice the maximum design tool frequency and run at 50 °C above its maximum operating temperature without error. The Configurable Intelligence Array is introduced as a low-overhead intelligence platform and used for a prototype neural circuit that can close the loop between a timing-fault detector and a programmable Phase Locked Loop (PLL) oscillator.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Keywords: | FPGA,NERVOUS SYSTEM,runtime management,adaptive systems,dark silicon,FAULT TOLERANCE,Autonomous systems,Bio-inspired Hardware,Social Insect Inspired Systems |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Funding Information: | Funder Grant number EPSRC EP/K040820/1 |
Depositing User: | Pure (York) |
Date Deposited: | 16 Dec 2020 13:40 |
Last Modified: | 27 Jan 2025 00:03 |
Status: | Published |
Publisher: | IEEE |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169099 |