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Multiobjective optimization of sleep vector for zigzag power-gated circuits in standard cell elements
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 45th annual Design Automation Conference table of contents
Anaheim, California
SESSION: Leakage analysis and optimization table of contents
Pages 600-605  
Year of Publication: 2008
ISBN ~ ISSN:0738-100X , 978-1-60558-115-6
Authors
Seungwhun Paik  KAIST, Daejeon, Korea
Youngsoo Shin  KAIST, Daejeon, Korea
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
: IEEE/CASS/CANDE/CEDA
: The EDA Consortium
Publisher
ACM  New York, NY, USA
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ABSTRACT

Zigzag power gating (ZPG) has been proposed to alleviate the drawback of power gating in its long wake-up delay, thereby broadening the application of power gating to suppressing active- as well as standby-leakage. However, complicated power network due to the use of nMOS and pMOS switches in zigzag fashion has limited its application to custom circuits. Heterogeneous use of power rails inevitably incurs overhead of area and wirelength during physical design. Furthermore, the use of sleep vector causes additional switching power when entering standby mode and returning back to active mode. The switching power should be minimized not to outweigh the leakage saving by employing ZPG scheme. In this paper, we propose a complete power network architecture, which allows us to use unmodified standard cell elements for implementing ZPG circuits. We formulate selecting sleep vector as a multi-objective optimization problem, minimizing transition energy and total wirelength. We solve the problem by employing multiobjective genetic-based algorithm. Experimental results show the saving of 39% in transition energy and 8% in wirelength, on average, for several benchmark circuits in 65-nm technology. The complete design flow starting from RTL description down to layout is proposed, and assessed with 65-nm technology.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Seungwhun Paik: colleagues
Youngsoo Shin: colleagues