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Author Tan, Lawrence ♦ Kaminsky, Michael ♦ Franklin, Jason ♦ Phanishayee, Amar ♦ Andersen, David G. ♦ Vasudevan, Vijay
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract This paper presents a fast array of wimpy nodes---FAWN---an approach for achieving low-power data-intensive data-center computing. FAWN couples low-power processors to small amounts of local flash storage, balancing computation and I/O capabilities. FAWN optimizes for per node energy efficiency to enable efficient, massively parallel access to data. The key contributions of this paper are the principles of the FAWN approach and the design and implementation of FAWN-KV---a consistent, replicated, highly available, and high-performance key-value storage system built on a FAWN prototype. Our design centers around purely log-structured datastores that provide the basis for high performance on flash storage, as well as for replication and consistency obtained using chain replication on a consistent hashing ring. Our evaluation demonstrates that FAWN clusters can handle roughly 350 key-value queries per Joule of energy---two orders of magnitude more than a disk-based system.
Description Affiliation: Intel Labs (Kaminsky, Michael) || Carnegie Mellon University (Andersen, David G.; Franklin, Jason; Phanishayee, Amar; Tan, Lawrence; Vasudevan, Vijay)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 54
Issue Number 7
Page Count 9
Starting Page 101
Ending Page 109

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Source: ACM Digital Library