DozzNoC: Reducing Static and Dynamic Energy in NoCs with Low-latency Voltage Regulators using Machine Learning

Mark Clark, Yingping Chen, Avinash Karanth, Brian Ma, Ahmed Louri

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

2 Scopus citations

Abstract

Network-on-chips (NoCs) continues to be the choice of communication fabric in multicore architectures because the NoC effectively combines the resource efficiency of the bus with the parallelizability of the crossbar. As NoC suffers from both high static and dynamic energy consumption, power-gating and dynamic voltage and frequency scaling (DVFS) have been proposed in the literature to improve energy-efficiency. In this work, we propose DozzNoC, an adaptable power management technique that effectively combines power-gating and DVFS techniques to target both static power and dynamic energy reduction with a single inductor multiple output (SIMO) voltage regulator. The proposed power management design is further enhanced by machine learning techniques that predict future traffic load for proactive DVFS mode selection. DozzNoC utilizes a SIMO voltage regulator scheme that allows for fast, low-powered, and independently power-gated or voltage scaled routers such that each router and its outgoing links share the same voltage/frequency domain. Our simulation results using PARSEC and Splash-2 benchmarks on an 8 × 8 mesh network show that for a decrease of 7% in throughput, we can achieve an average dynamic energy savings of 25% and an average static power reduction of 53%.

Original languageEnglish (US)
Title of host publicationProceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-11
Number of pages11
ISBN (Electronic)9781728168760
DOIs
StatePublished - May 2020
Externally publishedYes
Event34th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2020 - New Orleans, United States
Duration: May 18 2020May 22 2020

Publication series

NameProceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020

Conference

Conference34th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2020
Country/TerritoryUnited States
CityNew Orleans
Period5/18/205/22/20

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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