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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Barker, Kevin J. Kerbyson, Darren J. Anger, Eric |
| Copyright Year | 2014 |
| Abstract | While high performance has always been the primary constraint behind large-scale system design, future systems will be built with increasing energy efficiency in mind. Mechanisms such as fine-grained power scaling and gating will provide tools to system-software and application developers to ensure the most efficient use of tightly constrained power budgets. Such approaches to-date have been focused on node-level optimizations to impact overall system energy efficiency. In this work we introduce Dynamic Power Steering, in which power can be dynamically routed across a system to resources where it will be of most benefit and away from other resources to maintain a near-constant overall power budget. This, a higher-level algorithmic approach to improving energy efficiency, considers the whole extent of a system being used by an application. It can be used for applications in which there is load-imbalance that varies over its execution. Using two classes of applications, namely those that contain a wavefront type processing, and a particle-in-cell, we quantify the benefit of Dynamic Power Steering for a variety of workload characteristics and derive some insight into the ways in which workload behavior affect Power Steering applicability. |
| Starting Page | 60 |
| Ending Page | 69 |
| File Size | 1311150 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781479970360 |
| DOI | 10.1109/E2SC.2014.6 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-11-16 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Runtime Power distribution Dynamic scheduling Energy efficiency Power steering Resource management Optimization |
| Content Type | Text |
| Resource Type | Article |
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