Previous work has shown that intra-program optimizations, i.e., optimizations performed on individual programs in isolation, can be very effective in reducing disk energy in streaming applications. This paper investigates the potential additional benefits of inter-program optimizations where sets of programs are optimized together. Experimental results on different subsets of three streaming applications show that 7-49% additional energy savings (27.3% on average) can be obtained with negligible performance penalties using two novel inter-program optimizations, namely execution context sensitive buffer size selection and inverse barrier synchronization. These figures were obtained via physical measurements on two laptop disks.
In a pervasive computing environment, applications are able to run across different platforms with significantly different resources. Such platforms range from highperformance desktops to handheld PDAs. This paper discusses a compiler approach to reduce the energy consumption of a diskless device where the swap space is provided by a remotely mounted file system accessible via a wireless connection. Predicting swapping events at compile time allows effective energy management of a PDAs wireless communication component such as a 802.11 or Bluetooth card.The compiler activates and deactivates the communication card based on compile-time knowledge of the past and future memory footprint of an application. In contrast to OS techniques, the compiler can better predict future program behavior, and can change this behavior through program transformations that enable additional optimizations.A prototype compilation system EEL RM has been implemented as part of the SUIF2 compiler infrastructure. Preliminary experiments based on the SimpleScalar simulation toolset and three numerical programs indicate the potential benefits of the new technique.
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