Fractional Number Representation for the Digital Sintesi
Simplifying
Denis Ferreira Figueiredo
UNIVERSIDADE VEIGA DE ALMEIDA
Instituto de Ciência e Tecnologia – ICT – CINFO
Rua Ibituruna No. 108 - Maracanã
Rio de Janeiro - RJ - Cep: 20271-020
[email protected]
Prof. Luiz Biondi Neto
UNIVERSIDADE VEIGA DE ALMEIDA
Instituto de Ciência e Tecnologia – ICT – CINFO
Rua Ibituruna No. 108 - Maracanã
Rio de Janeiro - RJ - Cep: 20271-020
[email protected]
MSc. Eng. Fernando Hideo Fukuda
UNIVERSIDADE FEDERAL DO RIO DE JANEIRO (UFRJ-COPPE)
Núcleo de Transferência de Tecnologia (NTT)
[email protected]
ABSTRACT
The complex task of a Floating-Point Math
Unit implementation, well as their functional
performance is evaluated under a proposal of a
different point of view in computational
methodology, representation formats and their
primary functions. The use of the actual
Floating-Point Standards (IEEE 754) is put
under comparative view with more simple
math methods, with increased performance for
computational environments, as illustrated by
the numeric analysis and results, by the
adoption of fractional number representation
of REAL numbers, against the exponential
representation. That simplification in methods
being applied in the implementation, in a well
stable technological base, is able to represent
improvements of performance, and in
numerical math precision too. Under a
analysis of standard math benchmark models,
commonly used for math precision and speed
evaluation, can qualify the precision scope of
the two forms of numerical representation,
well as their calculation performances and
pondering the error propagation issues.
References
[1] IEEE 1987, IEEE STANDARD 754-1985
for Binary Floating–point Arithmetic,
IEEE, Reprinted in SIGPLAN 22(2) pp925.
[2] Brow, W. S. 1981. A simple but realistic
model of floating-point computation.
ACM trans. Math. Softw. 7,4, 445-480
[3] Courant, R. 2000, O que é matemática,
Robbins Herbert. Ed Ciência Moderna,
Rio de Janeiro, RJ, Brasil
[4] Cody, W. J. 1988. Floating-point
standards – theory and practice. In
reliability in Computing: The Role of
Interval Methods on Scientific Computing,
Ramon E. Moore. Ed. Academic Press,
Boston, Mass.
Numerical
Microsystems,
[5] Sun
Computation Guide Part no. 800-5277-10
(Rev. A, 22 Feb. 1991)
[6] INTEL, Intel Pentium Family User's
Manual, Volume 3: Architecture and
Programming Manual (1994) Order no.
241430
[7] ANSI 1978, American National Standard
Programming Language FORTRAN,
ANSI Standard X3.9-1978 American
National Standard, New York
[8] Goldberg, D., 1995, “What Every
Computer Scientist Should Know About
Floating-Point
Arithmetic”,
ACM
Computing Surveys 23, 1 (March 1991),
5-48. A version of it is reprinted in
SunPro’s Numerical Computation Guide.
151
Download

Fractional Number Represntation for the Digital Sintesi Simplification