Enhancing the performance of multi-cycle path analysis in an industrial setting

Hiroyuki Higuchi, Yusuke Matsunaga

Research output: Contribution to conferencePaper

9 Citations (Scopus)

Abstract

In this paper we enhance the performance of multi-cycle path analysis in an industrial setting. Industrial designs are, in general, more complicated, but contain more information than fundamental sequential circuits. We show how such information is used for improving the quality and the efficiency of multi-cycle path analysis. Specifically, we propose local FSM learning to take into account reachability information. We also propose FF enable learning to accelerate multi-cycle path analysis. Experimental results show that our methods can handle large industrial designs with tens of thousands of FFs and detects more multi-cycle paths faster than conventional ones.

Original languageEnglish
Pages192-197
Number of pages6
Publication statusPublished - Jun 1 2004
EventProceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004 - Yokohama, Japan
Duration: Jan 27 2004Jan 30 2004

Other

OtherProceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004
CountryJapan
CityYokohama
Period1/27/041/30/04

Fingerprint

Product design
Sequential circuits

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

Cite this

Higuchi, H., & Matsunaga, Y. (2004). Enhancing the performance of multi-cycle path analysis in an industrial setting. 192-197. Paper presented at Proceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004, Yokohama, Japan.

Enhancing the performance of multi-cycle path analysis in an industrial setting. / Higuchi, Hiroyuki; Matsunaga, Yusuke.

2004. 192-197 Paper presented at Proceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004, Yokohama, Japan.

Research output: Contribution to conferencePaper

Higuchi, H & Matsunaga, Y 2004, 'Enhancing the performance of multi-cycle path analysis in an industrial setting' Paper presented at Proceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004, Yokohama, Japan, 1/27/04 - 1/30/04, pp. 192-197.
Higuchi H, Matsunaga Y. Enhancing the performance of multi-cycle path analysis in an industrial setting. 2004. Paper presented at Proceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004, Yokohama, Japan.
Higuchi, Hiroyuki ; Matsunaga, Yusuke. / Enhancing the performance of multi-cycle path analysis in an industrial setting. Paper presented at Proceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004, Yokohama, Japan.6 p.
@conference{b7347921e5b340f5aecec396b305b77e,
title = "Enhancing the performance of multi-cycle path analysis in an industrial setting",
abstract = "In this paper we enhance the performance of multi-cycle path analysis in an industrial setting. Industrial designs are, in general, more complicated, but contain more information than fundamental sequential circuits. We show how such information is used for improving the quality and the efficiency of multi-cycle path analysis. Specifically, we propose local FSM learning to take into account reachability information. We also propose FF enable learning to accelerate multi-cycle path analysis. Experimental results show that our methods can handle large industrial designs with tens of thousands of FFs and detects more multi-cycle paths faster than conventional ones.",
author = "Hiroyuki Higuchi and Yusuke Matsunaga",
year = "2004",
month = "6",
day = "1",
language = "English",
pages = "192--197",
note = "Proceedings of the ASP - DAC 2004 Asia and South Pacific Design Automation Conference - 2004 ; Conference date: 27-01-2004 Through 30-01-2004",

}

TY - CONF

T1 - Enhancing the performance of multi-cycle path analysis in an industrial setting

AU - Higuchi, Hiroyuki

AU - Matsunaga, Yusuke

PY - 2004/6/1

Y1 - 2004/6/1

N2 - In this paper we enhance the performance of multi-cycle path analysis in an industrial setting. Industrial designs are, in general, more complicated, but contain more information than fundamental sequential circuits. We show how such information is used for improving the quality and the efficiency of multi-cycle path analysis. Specifically, we propose local FSM learning to take into account reachability information. We also propose FF enable learning to accelerate multi-cycle path analysis. Experimental results show that our methods can handle large industrial designs with tens of thousands of FFs and detects more multi-cycle paths faster than conventional ones.

AB - In this paper we enhance the performance of multi-cycle path analysis in an industrial setting. Industrial designs are, in general, more complicated, but contain more information than fundamental sequential circuits. We show how such information is used for improving the quality and the efficiency of multi-cycle path analysis. Specifically, we propose local FSM learning to take into account reachability information. We also propose FF enable learning to accelerate multi-cycle path analysis. Experimental results show that our methods can handle large industrial designs with tens of thousands of FFs and detects more multi-cycle paths faster than conventional ones.

UR - http://www.scopus.com/inward/record.url?scp=2442509031&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=2442509031&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:2442509031

SP - 192

EP - 197

ER -