Publications

Detailed Information

THOR: Orchestrated Thermal Management of Cores and Networks in 3D Many-Core Architectures

DC Field Value Language
dc.contributor.authorLee, Jinho-
dc.contributor.authorAhn, Junwhan-
dc.contributor.authorChoi, Kiyoung-
dc.contributor.authorKang, Kyungsu-
dc.date.accessioned2024-05-02T06:07:00Z-
dc.date.available2024-05-02T06:07:00Z-
dc.date.created2022-11-09-
dc.date.created2022-11-09-
dc.date.issued2015-01-
dc.identifier.citation2015 20TH ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE (ASP-DAC), pp.773-778-
dc.identifier.issn2153-6961-
dc.identifier.urihttps://hdl.handle.net/10371/200655-
dc.description.abstractMost previous researches on thermal management of many-core architectures focus on the control of either core resources or network resources only, even though both have significant thermal impacts. This paper proposes a holistic thermal management that applies dynamic voltage/frequency scaling to cores and routers together to maximize system performance under temperature constraint. The proposed method first determines a power budget given in aggregate weighted power for every pillar of vertically adjacent tiles. Then it performs voltage/frequency assignment under the budget while exploiting the characteristics of the applications. Experiments show that our approach outperforms existing methods.-
dc.language영어-
dc.publisherIEEE-
dc.titleTHOR: Orchestrated Thermal Management of Cores and Networks in 3D Many-Core Architectures-
dc.typeArticle-
dc.identifier.doi10.1109/ASPDAC.2015.7059104-
dc.citation.journaltitle2015 20TH ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE (ASP-DAC)-
dc.identifier.wosid000380442800147-
dc.identifier.scopusid2-s2.0-84926443065-
dc.citation.endpage778-
dc.citation.startpage773-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorLee, Jinho-
dc.contributor.affiliatedAuthorChoi, Kiyoung-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
Appears in Collections:
Files in This Item:
There are no files associated with this item.

Related Researcher

  • College of Engineering
  • Department of Electrical and Computer Engineering
Research Area AI Accelerators, Distributed Deep Learning, Neural Architecture Search

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share