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Performance Directed Energy Management for Main Memory and Disks
 

Summary: Performance Directed Energy Management
for Main Memory and Disks
XIAODONG LI, ZHENMIN LI, YUANYUAN ZHOU, and SARITA ADVE
University of Illinois at Urbana-Champaign
Much research has been conducted on energy management for memory and disks. Most studies use
control algorithms that dynamically transition devices to low power modes after they are idle for
a certain threshold period of time. The control algorithms used in the past have two major limita-
tions. First, they require painstaking, application-dependent manual tuning of their thresholds to
achieve energy savings without significantly degrading performance. Second, they do not provide
performance guarantees.
This article addresses these two limitations for both memory and disks, making memory/disk
energy-saving schemes practical enough to use in real systems. Specifically, we make four main con-
tributions. (1) We propose a technique that provides a performance guarantee for control algorithms.
We show that our method works well for all tested cases, even with previously proposed algorithms
that are not performance-aware. (2) We propose a new control algorithm, Performance-Directed
Dynamic (PD), that dynamically adjusts its thresholds periodically, based on available slack and
recent workload characteristics. For memory, PD consumes the least energy when compared to
previous hand-tuned algorithms combined with a performance guarantee. However, for disks, PD
is too complex and its self-tuning is unable to beat previous hand-tuned algorithms. (3) To improve
on PD, we propose a simpler, optimization-based, threshold-free control algorithm, Performance-

  

Source: Adve, Sarita - Department of Computer Science, University of Illinois at Urbana-Champaign

 

Collections: Computer Technologies and Information Sciences