Fine-Grained Energy Efficiency Using Per-Core DVFS with an Adaptive Runtime System

Bilge Acun, Kavitha Chandrasekar, Laxmikant V. Kale

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

Abstract

Dynamic voltage and frequency scaling (DVFS) is a well-known technique to reduce the power and/or energy consumption of various applications. While most processors provide chip-level DVFS, where the frequency and voltage of the cores in a chip can only be changed all together; core-level DVFS, where each core can be controlled independently, requires core-level voltage regulators in hardware and only is supported in production in Haswell generation among Intel processors. The finer grained control that per-core DVFS provides can lead to higher energy efficiency compared to chip-level DVFS especially for the unsynchronized, unstructured parallel applications when carefully applied. Ability to do per-core DVFS opens up new doors for different optimizations within runtime systems. We implement an intelligent energy efficient runtime module which uses a fine-grained function level per-core DVFS approach. Our module finds the energy-optimal frequency for each phase/function/kernel of the application over the first few iterations and applies the optimal frequency for each function. We test our implementation on Haswell processors and show that our algorithm enables 4% to 35% energy reduction over chip-level DVFS with as much as performance.

Original languageEnglish (US)
Title of host publication2019 10th International Green and Sustainable Computing Conference, IGSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728154169
DOIs
StatePublished - Oct 2019
Event10th International Green and Sustainable Computing Conference, IGSC 2019 - Alexandria, United States
Duration: Oct 21 2019Oct 24 2019

Publication series

Name2019 10th International Green and Sustainable Computing Conference, IGSC 2019

Conference

Conference10th International Green and Sustainable Computing Conference, IGSC 2019
CountryUnited States
CityAlexandria
Period10/21/1910/24/19

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Keywords

  • DVFS
  • energy efficiency
  • power
  • runtime systems

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Renewable Energy, Sustainability and the Environment

Cite this

Acun, B., Chandrasekar, K., & Kale, L. V. (2019). Fine-Grained Energy Efficiency Using Per-Core DVFS with an Adaptive Runtime System. In 2019 10th International Green and Sustainable Computing Conference, IGSC 2019 [8957174] (2019 10th International Green and Sustainable Computing Conference, IGSC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGSC48788.2019.8957174