FAWN: a fast array of wimpy nodes

  • Authors:

  • David G. Andersen;Jason Franklin;Michael Kaminsky;Amar Phanishayee;Lawrence Tan;Vijay Vasudevan

  • Affiliations:

  • Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Intel Labs, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA

  • Venue:
  • Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
  • Year:
  • 2009

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Abstract

This paper presents a new cluster architecture for low-power data-intensive computing. FAWN couples low-power embedded CPUs to small amounts of local flash storage, and balances computation and I/O capabilities to enable efficient, massively parallel access to data. The key contributions of this paper are the principles of the FAWN architecture 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.