Analyzing resource trade-offs in hardware overprovisioned supercomputers

Ryuichi Sakamoto, Tapasya Patki, Thang Cao, Masaaki Kondo, Koji Inoue, Masatsugu Ueda, Daniel Ellsworth, Barry Rountree, Martin Schulz

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

3 被引用数 (Scopus)

抄録

Hardware overprovisioned systems have recently been proposed as a viable alternative for a power-efficient design of next-generation supercomputers. A key challenge for such systems is to determine the degree of overprovisioning, which refers to the number of extra nodes that need to be installed under a given power constraint. In this paper, we first show that the degree of overprovisioning depends on dynamic parameters, such as the job mix as well as the global power constraint, and that static decisions can result in limited system throughput. We then study an exhaustive combination of adaptive resource management strategies that span three job scheduling algorithms, four power capping techniques, and three node boot-up mechanisms to understand the trade-off space involved. We then draw conclusions about how these strategies can adaptively control the degree of overprovisioning and analyze their impact on job throughput and power utilization.

本文言語英語
ホスト出版物のタイトルProceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ526-535
ページ数10
ISBN(印刷版)9781538643686
DOI
出版ステータス出版済み - 8 3 2018
外部発表はい
イベント32nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018 - Vancouver, カナダ
継続期間: 5 21 20185 25 2018

出版物シリーズ

名前Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018

その他

その他32nd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018
国/地域カナダ
CityVancouver
Period5/21/185/25/18

All Science Journal Classification (ASJC) codes

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ
  • 情報システムおよび情報管理

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