Interval arithmetic and computational science: Performance considerations

Alistair P. Rondell*, Bill Clarke, Josh Milthorpe

*Corresponding author for this work

    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, Proceedings
    PublisherSpringer Verlag
    Pages218-225
    Number of pages8
    ISBN (Print)3540343792, 9783540343790
    Publication statusPublished - 2006
    EventICCS 2006: 6th International Conference on Computational Science - Reading, United Kingdom
    Duration: 28 May 200631 May 2006

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume3991 LNCS - I
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    ConferenceICCS 2006: 6th International Conference on Computational Science
    Country/TerritoryUnited Kingdom
    CityReading
    Period28/05/0631/05/06

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