Design methodology for fine-grained leakage control in MTCMOS
Proceedings of the 2003 international symposium on Low power electronics and design
Proceedings of the 2003 international symposium on Low power electronics and design
A novel synthesis approach for active leakage power reduction using dynamic supply gating
Proceedings of the 42nd annual Design Automation Conference
Enhanced leakage reduction techniques using intermediate strength power gating
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Proceedings of the conference on Design, automation and test in Europe
Accurate energy breakeven time estimation for run-time power gating
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Leakage Control Through Fine-Grained Placement and Sizing of Sleep Transistors
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Energy attacks and defense techniques for wireless systems
Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks
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Runtime leakage control techniques, such as power gating (PG) and body biasing (BB), have been applied in a coarse-grained manner traditionally. In order to enable more aggressive leakage reduction, researchers are seeking ways to control leakage with finer granularity. Our research proposes two novel methods, namely circuit clustering for temporal and spatial idleness exploitation, to systematically reduce the granularity of leakage control and improve leakage reduction. Another strength of this paper is the quantitative study of leakage saving and control cost by leakage control with different granularity. With our quantitative study, designers can make the trade-off between leakage saving and control cost, and decide the optimum granularity for leakage control. A heuristic algorithm has been developed to automate the two circuit clustering methods and determine the optimum granularity for any given circuit. The analysis and experiments of this paper is mainly based on RBB. They are also applicable to PG by modifying the cost function.