@Article{chiu:smart-disks,
  author = {Steve C. Chiu and Wei-keng Liao and Alok N. Choudhary and Malmut T.
  Kandemir},
  title = {Processor-embedded distributed smart disks for {I/O}-intensive
  workloads: architectures, performance models and evaluation.},
  journal = {Journal of Parallel and Distributed Computing},
  year = {2004},
  month = {March},
  volume = {64},
  number = {3},
  pages = {427--445},
  institution = {Northwestern Univ, Dept Elect \& Comp Engn, Evanston, IL 60208
  USA; Northwestern Univ, Dept Elect \& Comp Engn, Evanston, IL 60208 USA; Penn
  State Univ, Dept Comp Sci \& Engn, University Pk, PA 16802 USA},
  publisher = {USA : Academic Press, 2004},
  copyright = {(c)2004 IEE; Institute for Scientific Information, Inc.},
  URL = {http://portal.acm.org/citation.cfm?id=1005485},
  keywords = {processor-embedded disks, smart disks, analytic performance
  models, I/O workload, pario-bib},
  abstract = {Processor-embedded disks, or smart disks, with their network
  interface controller, can in effect be viewed as processing elements with
  on-disk memory and secondary storage. The data sizes and access patterns of
  today's large I/O-intensive workloads require architectures whose processing
  power scales with increased storage capacity. To address this concern, we
  propose and evaluate disk-based distributed smart storage architectures.
  Based on analytically derived performance models, our evaluation with
  representative workloads show that offloading processing and performing
  point-to-point data communication improve performance over centralized
  architectures. Our results also demonstrate that distributed smart disk
  systems exhibit desirable scalability and can efficiently handle
  I/O-intensive workloads, such as commercial decision support database (TPC-H)
  queries, association rules mining, data clustering, and two-dimensional fast
  Fourier transform, among others. (15 refs.)}
}