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Software-Directed Disk Power Management for Scientific Applications

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3 Author(s)
Son, S.W. ; Dept. of Comput. Sci. & Eng., Pennsylvania State Univ., University Park, PA, USA ; Kandemir, M. ; Choudhary, A.

Disk power consumption is becoming an increasingly important issue in high-end servers that execute large-scale data-intensive applications. In particular, array-based scientific codes can spend a significant portion of their power budget on the disk subsystem. Observing this, the prior research proposed several strategies, such as spining down to low-power modes or adjusting the speed of the disk in lower RPM, to reduce power consumption on the disk subsystem. A common characteristic of most of these techniques is that they are reactive, in the sense that they make their decisions based on the disk access patterns observed during execution. While such techniques are certainly useful and the published studies reveal that they can be very effective in some cases, one can conceivably achieve better results by adopting a proactive scheme. Focusing on array-intensive scientific applications, this paper makes two important contributions. First, it presents a compiler-driven proactive approach to disk power management. In this approach, the compiler analyzes the application code and extracts the disk access pattern. It then uses this information to insert explicit disk power management calls in the appropriate places in the code. It also preactivates a disk (placed into the low-power mode) before it is actually needed to eliminate the potential performance impact of disk power management. The second contribution of this paper is a code transformation approach that can be used to increase the savings coming from a disk power management scheme (whether reactive or proactive). Our experimental results with several scientific application codes show that both the proactive disk power management approach and the disk layout aware code transformations are beneficial from both power consumption and execution time perspectives.

Published in:

Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International

Date of Conference:

04-08 April 2005

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