論文

査読有り
2017年6月

Minimizing detection-to-boosting latency toward low-power error-resilient circuits

INTEGRATION-THE VLSI JOURNAL
  • Chih-Cheng Hsu
  • ,
  • Masanori Hashimoto
  • ,
  • Mark Po-Hung Lin

58
開始ページ
236
終了ページ
244
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.vlsi.2017.01.002
出版者・発行元
ELSEVIER SCIENCE BV

Dynamic voltage scaling (DVS) has become one of the most effective approaches to achieve ultra-low-power SoC. To eliminate timing errors arising from DVS, several error-resilient circuit design techniques were proposed to detect and/or correct timing violations. The most recently proposed time-borrowing-and-local boosting (TBLB) technique has the advantage of lower power consumption and less performance degradation due to the needlessness of pipeline stalls. On the other hand, to make the best use of the TBLB technique, the latency from error detection to voltage boosting for TBLB latches must be carefully considered, especially during physical design. To address this issue, this paper first introduces the behavior of TBLB circuits, and then presents two major design styles of TBLB latches, including TBLB macros and multi-bit TBLB latches, for reducing detection-to-boosting latency. The corresponding physical synthesis methodologies for both design styles are further proposed. Experimental results based on the IWLS benchmarks show that the proposed physical synthesis approach for resilient circuits with multi-bit TBLB latches is very effective in reducing the delay of both combinational and error-detection circuits, which indicates better circuit reliability. To our best knowledge, this is the first work in the literature which introduces the physical synthesis methodologies for TBLB resilient circuits.

リンク情報
DOI
https://doi.org/10.1016/j.vlsi.2017.01.002
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000405052700024&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.vlsi.2017.01.002
  • ISSN : 0167-9260
  • eISSN : 1872-7522
  • Web of Science ID : WOS:000405052700024

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