LEAD: Learning-enabled energy-aware dynamic voltage/frequency scaling in NoCs

Mark Clark, Avinash Kodi, Razvan Bunescu, Ahmed Louri

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

5 Scopus citations

Abstract

Network on Chips (NoCs) are the interconnect fabric of choice for multicore processors due to their superiority over traditional buses and crossbars in terms of scalability. While NoC's offer several advantages, they still suffer from high static and dynamic power consumption. Dynamic Voltage and Frequency Scaling (DVFS) is a popular technique that allows dynamic energy to be saved, but it can potentially lead to loss in throughput. In this paper, we propose LEAD-Learning-enabled Energy-Aware Dynamic voltage/frequency scaling for NoC architectures wherein we use machine learning techniques to enable energy-performance trade-offs at reduced overhead cost. LEAD enables a proactive energy management strategy that relies on an offline trained regression model and provides a wide variety of voltage/frequency pairs (modes). LEAD groups each router and the router's outgoing links locally into the same V/F domain, allowing energy management at a finer granularity without additional timing complications and overhead. Our simulation results using PARSEC and Splash-2 benchmarks on a 4 × 4 concentrated mesh architecture show an average dynamic energy savings of 17% with a minimal loss of 4% in throughput and no latency increase.

Original languageEnglish (US)
Title of host publicationProceedings of the 55th Annual Design Automation Conference, DAC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
VolumePart F137710
ISBN (Print)9781450357005
DOIs
StatePublished - Jun 24 2018
Externally publishedYes
Event55th Annual Design Automation Conference, DAC 2018 - San Francisco, United States
Duration: Jun 24 2018Jun 29 2018

Other

Other55th Annual Design Automation Conference, DAC 2018
CountryUnited States
CitySan Francisco
Period6/24/186/29/18

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

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    Clark, M., Kodi, A., Bunescu, R., & Louri, A. (2018). LEAD: Learning-enabled energy-aware dynamic voltage/frequency scaling in NoCs. In Proceedings of the 55th Annual Design Automation Conference, DAC 2018 (Vol. Part F137710). [a82] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1145/3195970.3196068