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

doi:10.1109/MCSE.2011.30

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 › peer-review

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 language	English (US)
Article number	5725240
Pages (from-to)	83-87
Number of pages	5
Journal	Computing in Science and Engineering
Volume	13
Issue number	2
DOIs	https://doi.org/10.1109/MCSE.2011.30
State	Published - Mar 1 2011

Keywords

CUDA
GPUs
Graphics processing
Nvidia
scientific computing

ASJC Scopus subject areas

Computer Science(all)
Engineering(all)

Access to Document

10.1109/MCSE.2011.30

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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}",

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