Title
A sink-n-hoist framework for leakage power reduction
Abstract
Power leakage constitutes an increasing fraction of the total power consumption in modern semiconductor technologies. Recent research efforts have tried to integrate architecture and compiler solutions to employ power-gating mechanisms to reduce leakage power. This approach is to have compilers perform data-flow analysis and insert instructions at programs to shut down and wake up components whenever appropriate for power reductions. While this approach has been shown to be effective in early studies, there are concerns for the amount of power-control instructions being added to programs with the increasing amount of components equipped with power-gating control in a SoC design platform. In this paper, we present a Sink-N-Hoist framework in the compiler solution to generate balanced scheduling of power-gating instructions. Our solution will attempt to merge power-gating instructions as one compound instruction. Therefore, it will reduce the amount of power-gating instructions issued.We perform experiments by incorporating our compiler analysis and scheduling policies into SUIF compiler tools and by simulating the energy consumptions on Wattch toolkits. The experimental results demonstrate that our mechanisms are effective in reducing the amount of power-gating instructions while further in reducing leakage power compared to previous methods.
Year
DOI
Venue
2005
10.1145/1086228.1086252
EMSOFT
Keywords
Field
DocType
power-gating mechanism,leakage power reduction,power reduction,power-gating instruction,power-gating control,total power consumption,leakage power,compiler solution,sink-n-hoist framework,suif compiler tool,compiler analysis,power leakage,power control,data flow analysis
Computer science,Scheduling (computing),Leakage power,Hoist (device),Data-flow analysis,Real-time computing,Compiler,Merge (version control),Sink (computing),Embedded system,Power consumption
Conference
ISBN
Citations 
PageRank 
1-59593-091-4
9
0.77
References 
Authors
19
3
Name
Order
Citations
PageRank
Yi-Ping You114312.89
Chung-Wen Huang2375.91
Jenq Kuen Lee345948.71