What every computer scientist should know about floating-point arithmetic

Article Properties
  • Language
    English
  • Publication Date
    1991/03/01
  • Indian UGC (Journal)
  • Refrences
    32
  • Citations
    527
  • David Goldberg Xerox Palo Alto Research Center, Palo Alto, CA
Abstract
Cite
Goldberg, David. “What Every Computer Scientist Should Know about Floating-Point Arithmetic”. ACM Computing Surveys, vol. 23, no. 1, 1991, pp. 5-48, https://doi.org/10.1145/103162.103163.
Goldberg, D. (1991). What every computer scientist should know about floating-point arithmetic. ACM Computing Surveys, 23(1), 5-48. https://doi.org/10.1145/103162.103163
Goldberg D. What every computer scientist should know about floating-point arithmetic. ACM Computing Surveys. 1991;23(1):5-48.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Computer software
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Computer engineering
Computer hardware
Description

Are you sure your calculations are accurate? This tutorial addresses a critical but often overlooked aspect of computer science: floating-point arithmetic. It explains the direct impact on designers of computer systems due to floating-point. Floating-point is ubiquitous in computer systems and almost every language has a floating-point datatype. The paper begins with background on floating-point representation and rounding error, continues with a discussion of the IEEE floating-point standard, and concludes with examples of how computer system builders can better support floating point. It begins with background on floating-point representation and rounding error and continues with a discussion of the IEEE floating-point standard. Understanding floating-point arithmetic is crucial for computer scientists to ensure the reliability and accuracy of numerical computations in various applications. This tutorial empowers designers with the knowledge to build computer systems that better support floating-point operations, enhancing the overall quality and robustness of software and hardware systems. The tutorial concludes with examples of how computer system builders can better support floating point.

This tutorial published in ACM Computing Surveys aligns perfectly with the journal's goal of providing comprehensive overviews of important computing topics. By explaining the intricacies of floating-point arithmetic, this paper serves as a valuable resource for computer scientists.

Refrences
Citations
Citations Analysis
The first research to cite this article was titled The design of floating-point data types and was published in 1992. The most recent citation comes from a 2024 study titled The design of floating-point data types . This article reached its peak citation in 2020 , with 37 citations.It has been cited in 315 different journals, 14% of which are open access. Among related journals, the IEEE Transactions on Computers cited this research the most, with 22 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year