@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}",
note = "Funding Information: Nvidia donated the GPU hardware, QLogic donated part of the network hardware, and the US National Sci ence Foundation CNS 05-51665 grant partially paid for the node hardware; we thank them for their support. Several students working on independent study projects from the electrical and computer engineering, computer science, and chemistry departments greatly helped with the cluster assembly. Guo-chun Shi from the US National Center for Supercomputing Applications{\textquoteright} Innovative Systems Laboratory provided the MILC performance results.",
year = "2011",
month = mar,
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",
}