Minimizing Thermal Variation in Heterogeneous HPC Systems with FPGA Nodes

Yingyi Luo, Xiaoyang Wang, Seda Ogrenci Memik, Gokhan Memik, Kazutomo Yoshii, Pete Beckman

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

4 Scopus citations

Abstract

The presence of FPGAS in data centers has been growing due to their superior performance as accelerators. Thermal management, particularly battling the cooling cost in these high performance systems, is a primary concern. Introduction of new heterogeneous components only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is little explored. In this paper, we first show that the thermal behaviors of different FPGAS of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning based model to capture the thermal behavior of a multi-node FPGA cluster. We then propose to mitigate thermal variation and hotspots across the cluster by proactive task placement guided by our thermal model. Our experiments show that through proper placement of tasks on the multi-FPGA system, we can reduce the peak temperature by up to 11.50°C with no impact on performance.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages537-544
Number of pages8
ISBN (Electronic)9781538684771
DOIs
StatePublished - Jan 16 2019
Event36th International Conference on Computer Design, ICCD 2018 - Orlando, United States
Duration: Oct 7 2018Oct 10 2018

Publication series

NameProceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018

Conference

Conference36th International Conference on Computer Design, ICCD 2018
Country/TerritoryUnited States
CityOrlando
Period10/7/1810/10/18

Funding

ACKNOWLEDGMENT Results presented in this paper were obtained using the Chameleon testbed supported by the National Science Foundation.

Keywords

  • HPC
  • Task Placement
  • Thermal Modeling

ASJC Scopus subject areas

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

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