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Effective management of multiple configurable units using dynamic optimization

Authors:

Madhavi Valluri,

Lizy Kurian JohnAuthors Info & Claims

ACM Transactions on Architecture and Code Optimization (TACO), Volume 3, Issue 4

Pages 477 - 501

https://doi.org/10.1145/1187976.1187981

Published: 01 December 2006 Publication History

Abstract

As one of the promising efforts to minimize the surging microprocessor power consumption, adaptive computing environments (ACEs), where microarchitectural resources can be dynamically tuned to match a program's run-time requirement and characteristics, are becoming increasingly common. In an ACE, efficient management of the configurable units (CUs) is vital for maximizing the benefit of resource adaptation. ACEs usually have multiple configurable hardware units, necessitating exploration of a large number of combinatorial configurations in order to identify the most energy-efficient configuration. In this paper, we propose an ACE management framework for efficient management of multiple CUs, utilizing dynamic optimization systems' inherent capabilities of detecting and optimizing program hotspots, i.e., dominate code regions. We develop a scheme where hotpot boundaries are used for phase detection and adaptation. The framework achieves good energy reduction on managing multiple CUs with minimal hardware requirements and low implement cost by leveraging the existing infrastructure of a dynamic optimization system. The proposed framework is evaluated by dynamically adapting five CUs with distinct reconfiguration latencies and overheads. Those CUs are issue queue, reorder buffer, level-one data and instruction caches, and level-two cache. Previous research indicates that those five components dominate the energy consumption of a microprocessor. Despite the growing complexity and overhead of adapting five CUs, our technique reduces the energy consumption of those CUs by as much as 45%, while one of the best techniques provided by prior literature achieves less than 15% energy reduction for all CUs.

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Cited By

Munir AGordon-Ross ARanka S(2016)ReferencesModeling and Optimization of Parallel and Distributed Embedded Systems10.1002/9781119086383.refs(349-368)Online publication date: 8-Jan-2016
https://doi.org/10.1002/9781119086383.refs
Adegbija TGordon-Ross A(2013)Exploiting dynamic phase distance mapping for phase-based tuning of embedded systems2013 IEEE 31st International Conference on Computer Design (ICCD)10.1109/ICCD.2013.6657066(363-368)Online publication date: Oct-2013
https://doi.org/10.1109/ICCD.2013.6657066
Munir AGordon-Ross ALysecky SLysecky R(2013)A lightweight dynamic optimization methodology and application metrics estimation model for wireless sensor networksSustainable Computing: Informatics and Systems10.1016/j.suscom.2013.01.0033:2(94-108)Online publication date: Jun-2013
https://doi.org/10.1016/j.suscom.2013.01.003
Show More Cited By

Index Terms

Effective management of multiple configurable units using dynamic optimization
1. Software and its engineering
  1. Software notations and tools
    1. Compilers

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Published In

cover image ACM Transactions on Architecture and Code Optimization

ACM Transactions on Architecture and Code Optimization Volume 3, Issue 4

December 2006

169 pages

ISSN:1544-3566

EISSN:1544-3973

DOI:10.1145/1187976

Issue’s Table of Contents

Copyright © 2006 ACM.

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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Publication History

Published: 01 December 2006

Published in TACO Volume 3, Issue 4

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Cited By

Munir AGordon-Ross ARanka S(2016)ReferencesModeling and Optimization of Parallel and Distributed Embedded Systems10.1002/9781119086383.refs(349-368)Online publication date: 8-Jan-2016
https://doi.org/10.1002/9781119086383.refs
Adegbija TGordon-Ross A(2013)Exploiting dynamic phase distance mapping for phase-based tuning of embedded systems2013 IEEE 31st International Conference on Computer Design (ICCD)10.1109/ICCD.2013.6657066(363-368)Online publication date: Oct-2013
https://doi.org/10.1109/ICCD.2013.6657066
Munir AGordon-Ross ALysecky SLysecky R(2013)A lightweight dynamic optimization methodology and application metrics estimation model for wireless sensor networksSustainable Computing: Informatics and Systems10.1016/j.suscom.2013.01.0033:2(94-108)Online publication date: Jun-2013
https://doi.org/10.1016/j.suscom.2013.01.003
Munir AGordon-Ross A(2012)An MDP-Based Dynamic Optimization Methodology for Wireless Sensor NetworksIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2011.20823:4(616-625)Online publication date: 1-Apr-2012
https://dl.acm.org/doi/10.1109/TPDS.2011.208
Munir AGordon-Ross ALysecky SLysecky R(2012)Online algorithms for wireless sensor networks dynamic optimization2012 IEEE Consumer Communications and Networking Conference (CCNC)10.1109/CCNC.2012.6181082(180-187)Online publication date: Jan-2012
https://doi.org/10.1109/CCNC.2012.6181082
Munir AGordon-Ross ALysecky SLysecky R(2010)A lightweight dynamic optimization methodology for wireless sensor networks2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications10.1109/WIMOB.2010.5644982(129-136)Online publication date: Oct-2010
https://doi.org/10.1109/WIMOB.2010.5644982

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