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ISTC-CC Abstract
FAWN: A Fast Array of Wimpy Nodes
Communications of the ACM (CACM), Vol. 54, No. 7, pp. 101-109, July 2011.
David G. Andersen, Jason Franklin, Michael Kaminsky*, Amar Phanishayee,
Lawrence Tan, and Vijay Vasudevan
Carnegie Mellon University
*Intel Research Labs
This paper presents a fast array of wimpy nodes—FAWN— an approach for achieving low-power data-intensive datacenter 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.
FULL PAPER: pdf
