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Dividers

  • Jean-Pierre Deschamps
  • Gustavo D. Sutter
  • Enrique Cantó
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 149)

Abstract

Division is a basic arithmetic operation whose execution is based on 1-digit by m-digit multiplications and subtractions. Nevertheless, unlike addition and multiplication, division is generally not included as a predefined block within FPGA families. So, in many cases, the circuit designer will have to generate dividers by choosing some division algorithm and implementing it with adders and multipliers.

Keywords

FPGA Implementation Convergence Algorithm Complete Circuit Complement Representation Basic Arithmetic Operation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Freiman CV (1961) Statistical analysis of certain binary division algorithms. IRE Proc 49:91–103MathSciNetCrossRefGoogle Scholar
  2. 2.
    Robertson JE (1958) A new class of division methods. IRE Trans Electron Comput EC-7:218–222CrossRefGoogle Scholar
  3. 3.
    Cocke J, Sweeney DW (1957) High speed arithmetic in a parallel device. IBM technical report, Feb 1957Google Scholar
  4. 4.
    Deschamps JP, Sutter G (2010) Decimal division: algorithms and FPGA implementations. In: 6th southern conference on programmable logic (SPL)Google Scholar
  5. 5.
    Lang T, Nannarelli A (2007) A radix-10 digit-recurrence division unit: algorithm and architecture. IEEE Trans Comput 56(6):1–13MathSciNetCrossRefGoogle Scholar
  6. 6.
    Deschamps JP (2010) A radix-B divider. Contact: jp.deschamps@telefonica.netGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Jean-Pierre Deschamps
    • 1
  • Gustavo D. Sutter
    • 2
  • Enrique Cantó
    • 1
  1. 1.University Rovira i VirgiliTarragonaSpain
  2. 2.School of Computer EngineeringUniversidad Autonoma de MadridMadridSpain

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