On roundoff error distributions in floating point and logarithmic arithmetic

Jesse Louis Barlow, E. H. Bareiss

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

Probabilistic models of floating point and logarithmic arithmetic are constructed using assumptions with both theoretical and empirical justification. The justification of these assumptions resolves open questions in Hamming (1970) and Bustoz et al. (1979). These models are applied to errors from sums and inner products. A comparison is made between the error analysis properties of floating point and logarithmic computers. We conclude that the logarithmic computer has smaller error confidence intervals for roundoff errors than a floating point computer with the same computer word size and approximately the same number range.

Original languageEnglish (US)
Pages (from-to)325-347
Number of pages23
JournalComputing
Volume34
Issue number4
DOIs
StatePublished - Dec 1 1985

Fingerprint

Rounding error
Floating point
Logarithmic
Justification
Error Analysis
Scalar, inner or dot product
Probabilistic Model
Error analysis
Confidence interval
Resolve
Range of data
Model

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computational Theory and Mathematics

Cite this

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On roundoff error distributions in floating point and logarithmic arithmetic. / Barlow, Jesse Louis; Bareiss, E. H.

In: Computing, Vol. 34, No. 4, 01.12.1985, p. 325-347.

Research output: Contribution to journalArticle

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