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Balanced energy optimization

Published: 22 September 2004 Publication History

Abstract

Energy efficiency is now the number one issue for many systems, determining weight and cost, and constraining performance. Many techniques have been developed to minimize the dynamic and static power consumed by digital designs without any impact on functionality. To achieve further savings it is necessary to employ methods that do constrain functionality in some way. The designer must then balance increased energy efficiency with the functional implications of those techniques. Processing scalability can be employed to increase energy efficiency for workloads which vary dynamically. In single processor system this can be achieved using voltage and frequency scaling, and in multi-processor systems this can be supplemented with adaptive shutdown of unused processors. Scalability does imply a loss of system responsiveness when workloads transition from low to high levels, and this must be balanced against the increased energy efficiency achieved. Power efficiency can also be increased by optimising a processor for the application it is intended to run. By analyzing the algorithms to be executed it is possible to create a processor tailored to its workload. This loss of generality and flexibility must be balanced against the increased energy efficiency of a customized implementation. This talk describes work which ARM and its partners are doing to balance energy efficiency with functionality to create optimized designs.

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cover image ACM Conferences
CASES '04: Proceedings of the 2004 international conference on Compilers, architecture, and synthesis for embedded systems
September 2004
324 pages
ISBN:1581138903
DOI:10.1145/1023833
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 September 2004

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