A statistical model for system components selection

Author

Gupta, Varuna ; Mazouz, Abdelkader ; Agarwal, Ankur ; Hamza-Lup, Georgiana

Author_Institution

Coll. of Eng. & Comput. Sci., Florida Atlantic Univ., Boca Raton, FL, USA

fYear

2011

fDate

4-7 April 2011

Firstpage

1

Lastpage

6

Abstract

The proposed research is aimed at enhancing system design productivity by exploiting the principle of “design and reuse” to its full potential. Specifically, we present a statistical model for selecting from a component library the optimal components for a network-on-chip architecture such that to satisfy certain system performance requirements. Our model is based on regression analysis and Taguchi´s optimization technique. The model estimates the relationship between system performance and component attributes, to help the architect in the component selection process. Having such a model in the system design phase will allow the architect not only to make informed decisions when selecting components but also to exchange components with similar characteristics to fine tune system performance.

Keywords

Taguchi methods; logic design; network-on-chip; optimisation; regression analysis; statistical analysis; Taguchi optimization technique; component library; design and reuse principle; network-on-chip architecture; optimal components; regression analysis; statistical model; system components selection; system design phase; system design productivity enhancement; Analysis of variance; Analytical models; Data models; Mathematical model; Predictive models; Regression analysis; System performance; Taguchi optimization; component selection; network-on-chip; performance evaluation; regression analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems Conference (SysCon), 2011 IEEE International

Conference_Location

Montreal, QC

Print_ISBN

978-1-4244-9494-1

Type

conf

DOI

10.1109/SYSCON.2011.5929037

Filename

5929037