Neural network-based task scheduling with preemptive fan control

Bilge Acun, Eun Kyung Lee, Yoonho Park, Laxmikant V. Kale

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

Abstract

As cooling cost is a significant portion of the total operating cost of supercomputers, improving the efficiency of the cooling mechanisms can significantly reduce the cost. Two sources of cooling inefficiency in existing computing systems are discussed in this paper: temperature variations, and reactive fan speed control. To address these problems, we propose a learning-based approach using a neural network model to accurately predict core temperatures, a preemptive fan control mechanism, and a thermal-aware load balancing algorithm that uses the temperature prediction model. We demonstrate that temperature variations among cores can be reduced from 9°C to 2°C, and that peak fan power can be reduced by 61%. These savings are realized with minimal performance degradation.

Original languageEnglish (US)
Title of host publicationProceedings of E2SC 2016
Subtitle of host publication4th International Workshop on Energy Efficient Supercomputing - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-84
Number of pages8
ISBN (Electronic)9781509038565
DOIs
StatePublished - Jan 23 2017
Event4th International Workshop on Energy Efficient Supercomputing, E2SC 2016 - Salt Lake City, United States
Duration: Nov 14 2016 → …

Publication series

NameProceedings of E2SC 2016: 4th International Workshop on Energy Efficient Supercomputing - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis

Other

Other4th International Workshop on Energy Efficient Supercomputing, E2SC 2016
CountryUnited States
CitySalt Lake City
Period11/14/16 → …

Keywords

  • Fans
  • Neural networks
  • Power control
  • Supercomputers
  • Temperature control

ASJC Scopus subject areas

  • Hardware and Architecture

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  • Cite this

    Acun, B., Lee, E. K., Park, Y., & Kale, L. V. (2017). Neural network-based task scheduling with preemptive fan control. In Proceedings of E2SC 2016: 4th International Workshop on Energy Efficient Supercomputing - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 77-84). [7830512] (Proceedings of E2SC 2016: 4th International Workshop on Energy Efficient Supercomputing - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/E2SC.2016.016