Design and evaluation of the GeMTC framework for gpu-enabled many-task computing

Scott J. Krieder, Justin M. Wozniak, Timothy Armstrong, Michael Wilde, Daniel S. Katz, Benjamin Grimmer, Ian T. Foster, Oan Raicu

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

Abstract

We present the design and first performance and usability evaluation of GeMTC, a novel execution model and runtime system that enables accelerators to be programmed with many concurrent and independent tasks of potentially short or variable duration. With GeMTC, a broad class of such "many-task" applications can leverage the increasing number of accelerated and hybrid high-end computing systems. GeMTC overcomes the obstacles to using GPUs in a many-task manner by scheduling and launching independent tasks on hardware designed for SIMD-style vector processing. We demonstrate the use of a high-level MTC programming model (the Swift parallel dataflow language) to run tasks on many accelerators and thus provide a highproductivity programming model for the growing number of supercomputers that are accelerator-enabled. While still in an experimental stage, GeMTC can already support tasks of fine (subsecond) granularity and execute concurrent heterogeneous tasks on 86,000 independent GPU warps spanning 2.7M GPU threads on the Blue Waters supercomputer.

Original languageEnglish (US)
Title of host publicationHPDC 2014 - Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing
PublisherAssociation for Computing Machinery
Pages153-164
Number of pages12
ISBN (Print)9781450327480
DOIs
StatePublished - 2014
Externally publishedYes
Event23rd ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2014 - Vancouver, BC, Canada
Duration: Jun 23 2014Jun 27 2014

Publication series

NameHPDC 2014 - Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing

Other

Other23rd ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2014
Country/TerritoryCanada
CityVancouver, BC
Period6/23/146/27/14

Keywords

  • Accelerators
  • Cuda
  • Execution models
  • Gpgpu
  • Hybrid execution
  • Many-task computing
  • Programming models
  • Workflow

ASJC Scopus subject areas

  • Software

Fingerprint

Dive into the research topics of 'Design and evaluation of the GeMTC framework for gpu-enabled many-task computing'. Together they form a unique fingerprint.

Cite this