Title :
On the Feasibility of Dynamic Power Steering
Author :
Barker, Kevin J. ; Kerbyson, Darren J. ; Anger, Eric
Author_Institution :
Pacific Northwest Nat. Lab., Performance & Archit. Lab., Richland, WA, USA
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.
Keywords :
energy conservation; parallel processing; power aware computing; application developers; dynamic power steering; energy efficiency; higher-level algorithmic approach; large-scale system design; load imbalance; near-constant overall power budget; node-level optimization; particle-in-cell; system-software developers; tightly constrained power budgets; wavefront type processing; workload characteristics; Dynamic scheduling; Energy efficiency; Optimization; Power distribution; Power steering; Resource management; Runtime;
Conference_Titel :
Energy Efficient Supercomputing Workshop (E2SC), 2014
Conference_Location :
New Orleans, LA
DOI :
10.1109/E2SC.2014.6