Title :
Statistical Leakage Power Minimization Using Fast Equi-Slack Shell Based Optimization
Author :
Ye, Xiaoji ; Zhan, Yaping ; Li, Peng
Author_Institution :
Texas A&M Univ., College Station
Abstract :
Leakage power is becoming an increasingly important component of total chip power consumption for nanometer IC designs. Minimization of leakage power unavoidably enforces the consideration of the key sources of process variations, namely transistor channel length and threshold variations, since both have a significant impact on timing and leakage power. However, the statistical nature of chip performances often requires the use of expensive statistical analysis and optimization techniques in a leakage minimization task, contributing to high computational complexity. Further, the commonly used discrete cell libraries bring specific difficulty for design optimization and render pure continuous sizing and VT optimization algorithm suboptimal. In this paper, we present a fast yet effective approach to statistical leakage power reduction via gate sizing and multiple VT assignment. The proposed technique achieves the runtime efficiency via the use of the novel concept of equi-slack shells and performs fast leakage power reduction on the basis of shells while maintaining the timing yield. When combined with a finer grained gate-based post tuning step, the presented technique achieves Superior runtime efficiency while offering significant leakage power reduction.
Keywords :
electrical faults; integrated circuits; optimisation; equi-slack shell; leakage power reduction; nanometer IC designs; optimization; statistical leakage power minimization; total chip power consumption; transistor channel length; Algorithm design and analysis; Circuits; Constraint optimization; Design optimization; Energy consumption; Libraries; Robustness; Runtime; Statistical analysis; Timing; Design; Equi-slack shell; Leakage; Performance; Statistical Optimization; Verification; gorithms;
Conference_Titel :
Design Automation Conference, 2007. DAC '07. 44th ACM/IEEE
Print_ISBN :
978-1-59593-627-1