Leveraging FDSOI through body bias domain partitioning and bias search

Johannes Maximilian Kühn, Hideharu Amano, Oliver Bringmann, Wolfgang Rosenstiel

研究成果: Conference contribution

7 被引用数 (Scopus)


In FDSOI, sophisticated body biasing schemes can greatly reduce leakage or improve performance as well as efficiency. This paper proposes algorithms to determine body bias domain candidates which then merge those to reach a desired number of domains. Domain candidates are determined using an activation based approach, analyzing mapped verilog netlists to identify which parts of the design are used under specified conditions. Body bias domain partitionings are then determined based on activation and the timing of the partitioned parts. The algorithms include a body bias assignment algorithm to reach given timing goals with multiple domains and cross-domain resource sharing. The approach is compatible with any synthesis optimization and is resource sharing aware. Using an implementation of the proposed algorithms, overall leakage can be significantly reduced in all scenarios while obtaining the same benefits of body biasing. The method is evaluated in STMicro's 28nm FDSOI and Renesas's 65nm SOTB.

ホスト出版物のタイトルProceedings of the 53rd Annual Design Automation Conference, DAC 2016
出版社Institute of Electrical and Electronics Engineers Inc.
出版ステータスPublished - 2016 6月 5
イベント53rd Annual ACM IEEE Design Automation Conference, DAC 2016 - Austin, United States
継続期間: 2016 6月 52016 6月 9


名前Proceedings - Design Automation Conference


Other53rd Annual ACM IEEE Design Automation Conference, DAC 2016
国/地域United States

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 制御およびシステム工学
  • 電子工学および電気工学
  • モデリングとシミュレーション


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