GLoop: An event-driven runtime for consolidating GPGPU applications

Yusuke Suzuki, Hiroshi Yamada, Shinpei Kato, Kenji Kono

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

9 Citations (Scopus)


Graphics processing units (GPUs) have become an attractive platform for general-purpose computing (GPGPU) in various domains. Making GPUs a time-multiplexing resource is a key to consolidating GPGPU applications (apps) in multi-tenant cloud platforms. However, advanced GPGPU apps pose a new challenge for consolidation. Such highly functional GPGPU apps, referred to as GPU eaters, can easily monopolize a shared GPU and starve collocated GPGPU apps. This paper presents GLoop, which is a software run-time that enables us to consolidate GPGPU apps including GPU eaters. GLoop offers an event-driven programming model, which allows GLoop-based apps to inherit the GPU eaters' high functionality while proportionally scheduling them on a shared GPU in an isolated manner. We implemented a prototype of GLoop and ported eight GPU eaters on it. The experimental results demonstrate that our prototype successfully schedules the consolidated GPGPU apps on the basis of its scheduling policy and isolates resources among them.

Original languageEnglish
Title of host publicationSoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing
PublisherAssociation for Computing Machinery, Inc
Number of pages14
ISBN (Electronic)9781450350280
Publication statusPublished - 2017 Sept 24
Event2017 Symposium on Cloud Computing, SoCC 2017 - Santa Clara, United States
Duration: 2017 Sept 242017 Sept 27

Publication series

NameSoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing


Other2017 Symposium on Cloud Computing, SoCC 2017
Country/TerritoryUnited States
CitySanta Clara


  • Cloud computing
  • Operating systems

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science


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