Share Email Print

Proceedings Paper

Scheduling Linearly Indexed Assignment Codes
Author(s): T. Kailath; V. P. Roychowdhury
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

It has been recently shown that linearly indexed Assignment Codes can be efficiently used for coding several problems especially in signal processing and matrix algebra. In fact, mathematical expressions for many algorithms are directly in the form of linearly indexed codes, and examples include the formulas for matrix multiplication, any m-dimensional convolution/correlation, matrix transposition, and solving matrix Lyapunov's equation. Systematic procedures for converting linearly indexed Assignment Codes to localized algorithms that are closely related to Regular Iterative Algorithms (RIAs) have also been developed. These localized algorithms can be often efficiently scheduled by modeling them as RIAs; however, it is not always efficient to do so. In this paper we shall analyze and develop systematic procedures for determining efficient schedules directly for the linearly indexed ACs and the localized algorithms. We shall also illustrate our procedures by determining schedules for examples such as matrix transposition and Gauss-Jordan elimination algorithm.

Paper Details

Date Published: 17 May 1989
PDF: 12 pages
Proc. SPIE 1058, High Speed Computing II, (17 May 1989); doi: 10.1117/12.951674
Show Author Affiliations
T. Kailath, Stanford University (United States)
V. P. Roychowdhury, Stanford University (United States)

Published in SPIE Proceedings Vol. 1058:
High Speed Computing II
Keith Bromley, Editor(s)

© SPIE. Terms of Use
Back to Top