Power-Aware Software Prefetching

Authors:
Juan Chen;Yong Dong;Huizhan Yi;Xuejun Yang
Affiliations:
School of Computer, National University of Defense Technology, P.R. China;School of Computer, National University of Defense Technology, P.R. China;School of Computer, National University of Defense Technology, P.R. China;School of Computer, National University of Defense Technology, P.R. China
Venue:
ICESS '07 Proceedings of the 3rd international conference on Embedded Software and Systems
Year:
2007

Citing 7
Cited 1

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Tolerating latency through software-controlled data prefetching

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Wattch: a framework for architectural-level power analysis and optimizations

Proceedings of the 27th annual international symposium on Computer architecture
Design issues for dynamic voltage scaling

ISLPED '00 Proceedings of the 2000 international symposium on Low power electronics and design
Effective Hardware-Based Data Prefetching for High-Performance Processors

IEEE Transactions on Computers
Intraprogram dynamic voltage scaling: Bounding opportunities with analytic modeling

ACM Transactions on Architecture and Code Optimization (TACO)
Energy-Constrained prefetching optimization in embedded applications

EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing

Energy-efficient hardware data prefetching

IEEE Transactions on Very Large Scale Integration (VLSI) Systems

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Abstract

Some traditional optimizations improve the performance of pro-cessors, but consume the higher power dissipation. We study this trade-off using software prefetching as performance-oriented optimization technique. We first demonstrate that software prefetching provides a significant performance boost with the higher power on several memory-intensive benchmarks. However, when we combine software prefetching with dynamic voltage/frequency scaling (DVFS), the performance gain can be achieved without power increase, which is called a power-aware approach. Besides reducing power dissipation through DVFS, we also improve the performance through adjusting the prefetch distance. A modified SimpleScalar/Wattch is used to evaluate our power-aware software prefetching. Experimental results show this optimization approach is effective to guarantee no power increase due to prefetching and improve the performance of software prefetching.