Fast floating point vectoring algorithms and performance evaluation

Author

Lee, Jeong-A ; van der Kolk, Kees-Jan

Author_Institution

Dept. of Comput. Sci., Chosun Univ., Kwang-Ju, South Korea

Volume

2

fYear

1999

fDate

24-27 Oct. 1999

Firstpage

1356

Abstract

In this paper, we briefly introduce our previous work-the formalization of fast rotation-based vectorization algorithms-and show how to obtain key parameters such as window size for the implementation by extensive simulation. We also show that, if the angle selection techniques presented in this paper are used in an approximate rotation setup, such as in a Jacobi based eigenvalue decomposition (EVD) algorithm, we can profit from the fact that the average latency of the vectoring unit is significantly reduced.

Keywords

eigenvalues and eigenfunctions; floating point arithmetic; performance evaluation; vectors; Jacobi based eigenvalue decomposition algorithm; angle selection techniques; approximate rotation setup; average latency; fast floating point vectoring algorithms; fast rotation-based vectorization algorithm; performance evaluation; window size; Arithmetic; Cities and towns; Computer science; Content addressable storage; Delay; Eigenvalues and eigenfunctions; Fast Fourier transforms; Jacobian matrices; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-5700-0

Type

conf

DOI

10.1109/ACSSC.1999.831928

Filename

831928