• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

DMCA

External Memory Algorithms and Data Structures (1998)

Cached

  • Download as a PDF

Download Links

  • [www.cs.duke.edu]
  • [www.cs.duke.edu]
  • [www.mpi-inf.mpg.de]
  • [www.cs.duke.edu]
  • [www.cs.duke.edu]
  • [www.cs.duke.edu]
  • [www.cs.duke.edu]
  • [verona.dei.unipd.it]
  • [simon.cs.cornell.edu]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Jeffrey Scott Vitter
Citations:349 - 23 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Vitter98externalmemory,
    author = {Jeffrey Scott Vitter},
    title = { External Memory Algorithms and Data Structures},
    year = {1998}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

Data sets in large applications are often too massive to fit completely inside the computer's internal memory. The resulting input/output communication (or I/O) between fast internal memory and slower external memory (such as disks) can be a major performance bottleneck. In this paper, we survey the state of the art in the design and analysis of external memory algorithms and data structures (which are sometimes referred to as "EM" or "I/O" or "out-of-core" algorithms and data structures). EM algorithms and data structures are often designed and analyzed using the parallel disk model (PDM). The three machine-independent measures of performance in PDM are the number of I/O operations, the CPU time, and the amount of disk space. PDM allows for multiple disks (or disk arrays) and parallel CPUs, and it can be generalized to handle tertiary storage and hierarchical memory. We discuss several important paradigms for how to solve batched and online problems efficiently in external memory. Programming tools and environments are available for simplifying the programming task. The TPIE system (Transparent Parallel I/O programming Environment) is both easy to use and efficient in terms of execution speed. We report on some experiments using TPIE in the domain of spatial databases. The newly developed EM algorithms and data structures that incorporate the paradigms we discuss are significantly faster than methods currently used in practice.

Keyphrases

data structure    external memory algorithm    external memory    em algorithm    machine-independent measure    out-of-core algorithm    hierarchical memory    several important paradigm    large application    cpu time    programming task    programming tool    disk space    fast internal memory    transparent parallel    parallel disk model    major performance bottleneck    spatial database    online problem    tertiary storage    tpie system    multiple disk    parallel cpu    execution speed    data set    input output communication    internal memory   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University