Efficient multi-layer obstacle-avoiding preferred direction rectilinear Steiner tree construction

Jia Ru Chuang, Jai Ming Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Constructing rectilinear Steiner trees for signal nets is a very important procedure for placement and routing because we can use it to find topologies of nets and measure the design quality. However, in modern VLSI designs, pins are located in multiple routing layers, each routing layer has its own preferred direction, and there exist numerous routing obstacles incurred from IP blocks, power networks, pre-routed nets, etc, which make us need to consider multilayer obstacle-avoiding preferred direction rectilinear Steiner minimal tree (ML-OAPDRSMT) problem. This significantly increases the complexity of the problem, and an efficient and effective algorithm to deal with the problem is desired. In this paper, we propose a very simple and effective approach to deal with ML-OAPDRSMT problem. Unlike previous works usually build a spanning graph and find a spanning tree to deal with this problem, which takes a lot of time, we first determine a connection ordering for all pins, and then iteratively connect every two neighboring pins by a greedy heuristic algorithm. The experimental results show that our method has average 5.78% improvement over [7] and at least five times speed up comparing with their approach.

Original languageEnglish
Title of host publication2011 16th Asia and South Pacific Design Automation Conference, ASP-DAC 2011
Pages527-532
Number of pages6
DOIs
Publication statusPublished - 2011 Mar 28
Event2011 16th Asia and South Pacific Design Automation Conference, ASP-DAC 2011 - Yokohama, Japan
Duration: 2011 Jan 252011 Jan 28

Publication series

NameProceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC

Other

Other2011 16th Asia and South Pacific Design Automation Conference, ASP-DAC 2011
CountryJapan
CityYokohama
Period11-01-2511-01-28

All Science Journal Classification (ASJC) codes

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

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