NDLI: An evaluation of code and data optimizations in the context of disk power reduction

Content Provider	IEEE Xplore Digital Library
Author	Kandemir, M. Seung Woo Son Guangyu Chen
Copyright Year	2005
Description	Author affiliation: Comput. Sci. & Eng. Dept., Pennsylvania State Univ., University Park, PA, USA (Kandemir, M.; Seung Woo Son; Guangyu Chen)
Abstract	Disk power management is becoming increasingly important in high-end server and cluster type of environments that execute data-intensive applications. While hardware-only approaches (e.g., low-power modes supported by current disks) are successful to a certain extent, one also needs to consider the software side to achieve further energy savings. This paper first demonstrates that conventional data locality oriented code transformations are not sufficient for minimizing disk power consumption. The reason is that these optimizations do not take into account how disk-resident array data are laid out on the disk system, and consequently, fail to increase idle periods of disks, which is the primary metric using which disk power can be reduced. Instead, we propose a disk layout aware application optimization strategy that uses both code restructuring and data layout optimization. Our experimental evaluation with several benchmark codes reveal that the proposed strategy is very successful in reducing disk energy consumption without performing much worse than a pure data locality oriented scheme, as far as execution cycles are concerned. The experiments also show that the benefits coming from our approach increase with the increased number of disks; i.e., it scales very well.
Sponsorship	ACM SIGDA IEEE Circuits and Syst. Soc
Starting Page	209
Ending Page	214
File Size	1406025
Page Count	6
File Format	PDF
ISBN	1595931376
DOI	10.1109/LPE.2005.195516
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-08-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Association for Computing Machinery, Inc. (ACM)
Subject Keyword	Energy consumption Optimizing compilers Space technology Permission Computer science Data engineering Power engineering and energy Energy management Environmental management Engineering management
Content Type	Text
Resource Type	Article

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