https://scholars.lib.ntu.edu.tw/handle/123456789/607142
標題: | DATC RDF-2021: Design Flow and Beyond | 作者: | Chen J Jung J Kahng A.B Kim S Kravets V.N Li Y.-L Varadarajan R Woo M. HUI-RU JIANG |
關鍵字: | Resource Description Framework (RDF);Calibration data;Design flows;Flow robust;Future research directions;Generator design;Machine learning applications;Metric standards;Robust designs;Design for testability | 公開日期: | 2021 | 卷: | 2021-November | 來源出版物: | IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD | 摘要: | This paper describes the latest release of the DATC Robust Design Flow (RDF), RDF-2021, which has several key additions to expand its horizons. The Chisel/FIRRTL compiler is now part of DATC RDF, enabling support of recent hardware generator designs written in Chisel. Logic locking through RTL obfuscation, an updated ABC synthesis flow, and DFT support are other notable updates to the RDF. A Bookshelf-LEF/DEF converter powered by OpenDB is also added into DATC RDF’s inventory as an enabler of robust benchmark conversion. We also describe efforts toward open metrics standards and datasets for machine learning (ML) applications and smart tuning of the design flow, as well as expansion of public analysis calibration data. Our paper closes with future research directions related to DATC’s efforts. ? 2021 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124146677&doi=10.1109%2fICCAD51958.2021.9643553&partnerID=40&md5=cdcaa6ce6e8b4c5de00223bed5696726 https://scholars.lib.ntu.edu.tw/handle/123456789/607142 |
ISSN: | 10923152 | DOI: | 10.1109/ICCAD51958.2021.9643553 |
顯示於: | 電機工程學系 |
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