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

@article{0a2ae6898cb34bfa98701dbab517bd27,
title = "EcoG: A power-efficient GPU cluster architecture for scientific computing",
abstract = "Researchers built the EcoG GPU-based cluster to show that a system can be designed around GPU computing and still be power efficient.",
keywords = "CUDA, GPUs, Graphics processing, Nvidia, scientific computing",
author = "Mike Showerman and Enos, {Jeremy James} and Steffen, {Craig Philip} and Sean Treichler and Gropp, {William D} and Hwu, {Wen-Mei W}",
year = "2011",
month = "3",
day = "1",
doi = "10.1109/MCSE.2011.30",
language = "English (US)",
volume = "13",
pages = "83--87",
journal = "Computing in Science and Engineering",
issn = "1521-9615",
publisher = "IEEE Computer Society",
number = "2",

}

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AU - Hwu, Wen-Mei W

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N2 - Researchers built the EcoG GPU-based cluster to show that a system can be designed around GPU computing and still be power efficient.

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

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KW - GPUs

KW - Graphics processing

KW - Nvidia

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