TY - GEN
T1 - Leveraging FDSOI through body bias domain partitioning and bias search
AU - Kühn, Johannes Maximilian
AU - Amano, Hideharu
AU - Bringmann, Oliver
AU - Rosenstiel, Wolfgang
N1 - Funding Information:
Furthermore, this work was partially funded by DFG under RO-1030/13 within the Priority Program 1500 and the Things2DO project BMBF 16ES0247.
Publisher Copyright:
© 2016 ACM.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/6/5
Y1 - 2016/6/5
N2 - 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.
AB - 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.
KW - Body biasing
KW - Domain partitioning
KW - FDSOI
KW - Leakage optimization
UR - http://www.scopus.com/inward/record.url?scp=84977119397&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84977119397&partnerID=8YFLogxK
U2 - 10.1145/2897937.2898039
DO - 10.1145/2897937.2898039
M3 - Conference contribution
AN - SCOPUS:84977119397
T3 - Proceedings - Design Automation Conference
BT - Proceedings of the 53rd Annual Design Automation Conference, DAC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 53rd Annual ACM IEEE Design Automation Conference, DAC 2016
Y2 - 5 June 2016 through 9 June 2016
ER -