EcoG: A power-efficient GPU cluster architecture for scientific computing

Mike Showerman, Jeremy James Enos, Craig Philip Steffen, Sean Treichler, William D Gropp, Wen-Mei W Hwu

Research output: Contribution to journal › Article

Abstract

Researchers built the EcoG GPU-based cluster to show that a system can be designed around GPU computing and still be power efficient.

Original languageEnglish (US)
Article number5725240
Pages (from-to)83-87
Number of pages5
JournalComputing in Science and Engineering
Volume13
Issue number2
DOIs
StatePublished - Mar 1 2011

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Natural sciences computing
Graphics processing unit

Keywords

  • CUDA
  • GPUs
  • Graphics processing
  • Nvidia
  • scientific computing

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Cite this

EcoG : A power-efficient GPU cluster architecture for scientific computing. / Showerman, Mike; Enos, Jeremy James; Steffen, Craig Philip; Treichler, Sean; Gropp, William D; Hwu, Wen-Mei W.

In: Computing in Science and Engineering, Vol. 13, No. 2, 5725240, 01.03.2011, p. 83-87.

Research output: Contribution to journal › Article

Showerman, M, Enos, JJ, Steffen, CP, Treichler, S, Gropp, WD & Hwu, W-MW 2011, 'EcoG: A power-efficient GPU cluster architecture for scientific computing', Computing in Science and Engineering, vol. 13, no. 2, 5725240, pp. 83-87. https://doi.org/10.1109/MCSE.2011.30
Showerman M, Enos JJ, Steffen CP, Treichler S, Gropp WD, Hwu W-MW. EcoG: A power-efficient GPU cluster architecture for scientific computing. Computing in Science and Engineering. 2011 Mar 1;13(2):83-87. 5725240. https://doi.org/10.1109/MCSE.2011.30
Showerman, Mike ; Enos, Jeremy James ; Steffen, Craig Philip ; Treichler, Sean ; Gropp, William D ; Hwu, Wen-Mei W. / EcoG : A power-efficient GPU cluster architecture for scientific computing. In: Computing in Science and Engineering. 2011 ; Vol. 13, No. 2. pp. 83-87.
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