NDLI: Impact of virtual execution environments on processor energy consumption and hardware adaptation

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Content Provider	ACM Digital Library
Author	Hu, Shiwen John, Lizy K.
Abstract	During recent years, microprocessor energy consumption has been surging and efforts to reduce power and energy have received a lot of attention. At the same time, virtual execution environments (VEEs), such as Java virtual machines, have grown in popularity. Hence, it is important to evaluate the impact of virtual execution environments on microprocessor energy consumption. This paper characterizes the energy and power impact of two important components of VEEs, Just-in-time(JIT) optimization and garbage collection. We find that by reducing instruction counts, JIT optimization significantly reduces energy consumption, while garbage collection incurs runtime overhead that consumes more energy. Importantly, both JIT optimization and garbage collection decrease the average power dissipated by a program. Detailed analysis reveals that both JIT optimizer and JIT optimized code dissipate less power than un-optimized code. On the other hand, being memory bound and with low ILP, the garbage collector dissipates less power than the application code, but rarely affects the average power of the latter.Adaptive microarchitectures are another recent trend for energy reduction where microarchitectural resources can be dynamically tuned to match program runtime requirements. This research reveals that both JIT optimization and garbage collection alter a program's behavior and runtime requirements, which considerably affects the adaptation of configurable hardware units, and influences the overall energy consumption. This work also demonstrates that the adaptation preferences of the two VEE services differ substantially from those of the application code. Both VEE services prefer a simple core for high energy reduction. On the other hand, the JIT optimizer usually requires larger data caches, while the garbage collector rarely benefits from large data caches. The insights gained in this paper point to novel techniques that can further reduce microprocessor energy consumption.
Starting Page	100
Ending Page	110
Page Count	11
File Format	PDF
ISBN	1595933328
DOI	10.1145/1134760.1134775
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2006-06-14
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Hardware adaptation Energy efficiency Power dissipation
Content Type	Text
Resource Type	Article

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