Improving dynamic voltage scaling algorithms with PACE
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Dynamic voltage scaling for multitasking real-time systems with uncertain execution time
GLSVLSI '06 Proceedings of the 16th ACM Great Lakes symposium on VLSI
Runtime distribution-aware dynamic voltage scaling
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Dynamic voltage frequency scaling for multi-tasking systems using online learning
ISLPED '07 Proceedings of the 2007 international symposium on Low power electronics and design
Dynamic voltage scaling of supply and body bias exploiting software runtime distribution
Proceedings of the conference on Design, automation and test in Europe
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Program phase and runtime distribution-aware online DVFS for combined Vdd/Vbb scaling
Proceedings of the Conference on Design, Automation and Test in Europe
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Temperature and supply Voltage aware performance and power modeling at microarchitecture level
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Optimal intratask dynamic voltage-scaling technique and its practical extensions
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Success of workload prediction, which is critical in achieving low energy consumption via dynamic voltage and frequency scaling (DVFS), depends on the accuracy of modeling the major sources of workload variation. Among them, memory stall time, whose variation is significant especially in case of memory-bound applications, has been mostly neglected or handled in too simplistic assumptions in previous works. In this paper, we present an analytical DVFS method which takes into account variations in both computation and memory stall cycles. The proposed method reduces leakage power consumption as well as switching power consumption through combined Vdd/Vbb scaling. Experimental results on MPEG4 and H.264 decoder have shown that, compared to previous methods [3] and [6], our method achieves up to additional 30.0% and 15.8% energy reductions, respectively.