An Efficient Architecture for Double Precision Floating Point Adder with LOA

Authors

  • S. Rajasekhar Reddy  M.Tech Scholar, ECE Department, CIET, Guntur, Andhra Pradesh, India
  • M. Kalapana Chowdary  Assistant. Professor, ECE Department, CIET, Guntur, Andhra Pradesh, India
  • P. Kanvitha  M.Tech Scholar, ECE Department, CIET, Guntur, Andhra Pradesh, India

Keywords:

Double Precision, Floating-Point Adders, Area Efficient.

Abstract

Because of dynamic representation capabilities and a large spectrum of numbers can be represented with a limited number of bits, floating-point numbers are being widely adopted in the fields of scientific applications. A floating-point arithmetic unit is specifically designed to carry out on floating-point numbers and is one of the most common parts of any computing system in the area of binary applications. Floating-point additions are the most frequent floating-point operations and floating-point adders are therefore critically important components in signal processing and embedded platforms. This review paper presents the survey of related works of different algorithms/techniques which are important for implementation of double precision floating point adder with reduced delay based on FPGAs. In this paper, an area and delay efficient floating-point adder are proposed by approximately designing an exponent subtractor and mantissa adder. Related operations such as normalization and rounding are also dealt with in terms of inexact computing.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2017-08-31

Issue

Volume 3, Issue 5, July-August-2017

Section

Research Articles

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Copyright (c) IJSRSET

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
S. Rajasekhar Reddy, M. Kalapana Chowdary, P. Kanvitha "An Efficient Architecture for Double Precision Floating Point Adder with LOA" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 5, pp.551-555, July-August-2017.