Interval Arithmetic and Computational Science: Performance Considerations

Alistair P. Rendell, Bill Clarke, Josh Milthorpe

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Interval analysis is an alternative to conventional floating-point computations that offers guaranteed error bounds. Despite this advantage, interval methods have not gained widespread use in large scale computational science applications. This paper addresses this issue from a performance perspective, comparing the performance of floating point and interval operations for some small computational kernels. Particularly attention is given to the Sun Fortran interval implementation, although the strategies introduced here to enhance performance are applicable to other interval implementations. Fundamental differences in the operation counts and memory references requirements of interval and floating point codes are discussed.
Original languageEnglish
Title of host publicationComputational Science – ICCS 2006
Subtitle of host publication6th International Conference, Reading, UK, May 28-31, 2006, Proceedings, Part I
EditorsVassil N. Alexandrov, Geert Dick van Albada, Peter M. A. Sloot, Jack Dongarra
PublisherSpringer
Pages218-225
Number of pages8
ISBN (Electronic)978-3-540-34380-6
ISBN (Print)978-3-540-34379-0
DOIs
Publication statusPublished - 2006
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
PublisherSpringer, Berlin, Heidelberg
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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