AMNESIAC: Amnesic automatic computer trading computation for communication for energy efficiency

Ismail Akturk, Ulya R. Karpuzcu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Due to imbalances in technology scaling, the energy consumption of data storage and communication by far exceeds the energy consumption of actual data production, i.e., computation. As a consequence, recomputing data can become more energy-efficient than storing and retrieving precomputed data. At the same time, recomputation can relax the pressure on the memory hierarchy and the communication bandwidth. This study hence assesses the energy efficiency prospects of trading computation for communication. We introduce an illustrative proof-of-concept design, identify practical limitations, and provide design guidelines.

Original languageEnglish (US)
Title of host publicationASPLOS 2017 - 22nd International Conference on Architectural Support for Programming Languages and Operating Systems
PublisherAssociation for Computing Machinery
Pages811-824
Number of pages14
Volume52
Edition4
ISBN (Electronic)9781450344654
DOIs
StatePublished - Apr 4 2017
Event22nd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2017 - Xi'an, China
Duration: Apr 8 2017Apr 12 2017

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
VolumePart F127193

Other

Other22nd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2017
CountryChina
CityXi'an
Period4/8/174/12/17

Bibliographical note

Publisher Copyright:
© 2017 ACM.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Keywords

  • Energy efficiency
  • Recomputation

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