Effectiveness of reverse body bias for leakage control in scaled dual Vt CMOS ICs
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Task scheduling and voltage selection for energy minimization
Proceedings of the 39th annual Design Automation Conference
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Proceedings of the conference on Design, automation and test in Europe
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Power-Aware Scheduling for Periodic Real-Time Tasks
IEEE Transactions on Computers
Proceedings of the 44th annual Design Automation Conference
Energy minimization for real-time systems with non-convex and discrete operation modes
Proceedings of the Conference on Design, Automation and Test in Europe
Transition-aware task scheduling and configuration selection in reconfigurable embedded systems
ACM SIGBED Review - Special Issue on the 5th Workshop on Adaptive and Reconfigurable Embedded Systems
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Dynamic voltage/frequency scaling (DVFS) and adaptive body biasing (ABB) have shown to effectively reduce dynamic and leakage energy consumption in real-time embedded systems. Although these techniques exploit the slack time on a given task ordering, the task ordering may not provide a slack time distribution that DVFS/ABB can benefit from and this can limit the potential energy saving such techniques can provide. In this paper, we present an optimal network flow based solution for simultaneous static real-time scheduling and energy minimization (DVFS and ABB) on multiprocessors. Results show that our optimal solution reduces the energy dissipation by 47.84%, 26.21% and 17.46%, on average, in comparison with no-DVFS execution, voltage scaling algorithm with virtual continuous speed [1] and an optimal energy minimization algorithm without task re-ordering[2], respectively.