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

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

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Keywords

CUDA
GPUs
Graphics processing
Nvidia
scientific computing

ASJC Scopus subject areas

Computer Science(all)
Engineering(all)

Cite this

Showerman, M., Enos, J. J., Steffen, C. P., Treichler, S., Gropp, W. D., & Hwu, W-M. W. (2011). EcoG: A power-efficient GPU cluster architecture for scientific computing. Computing in Science and Engineering, 13(2), 83-87. [5725240]. https://doi.org/10.1109/MCSE.2011.30

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Access to Document

10.1109/MCSE.2011.30