An approach to channel routing problem using neural networks

1990 ◽  
Vol 73 (8) ◽  
pp. 52-63 ◽  
Author(s):  
Takashi Shimamoto ◽  
Akio Sakamoto
Keyword(s):  
Neural Networks ◽  
Channel Routing ◽  
Routing Problem

An application of neural networks on channel routing problem

1991 ◽  
Vol 17 (2-3) ◽  
pp. 229-240 ◽  
Author(s):  
Pao-Hsu Shih ◽  
Wu-Shung Feng
Keyword(s):  
Neural Networks ◽  
Channel Routing ◽  
Routing Problem

scholarly journals An Optimum Channel Routing Algorithm in the Knock-knee Diagonal Model

VLSI Design ◽  
1994 ◽  
Vol 1 (3) ◽  
pp. 233-242 ◽  
Author(s):  
Xiaoyu Song
Keyword(s):  
Routing Algorithm ◽  
Difficult Problem ◽  
Layout Design ◽  
Channel Routing ◽  
Routing Problem ◽  
Vlsi Layout ◽  
Channel Density ◽  
Optimum Algorithm ◽  
Important Time ◽  
Optimum Channel

Channel routing problem is an important, time consuming and difficult problem in VLSI layout design. In this paper, we consider the two-terminal channel routing problem in a new routing model, called knock-knee diagonal model, where the grid consists of right and left tracks displayed at +45° and –45°. An optimum algorithm is presented, which obtains d + 1 as an upper bound to the channel width, where d is the channel density.

scholarly journals On the restrictive channel thickness estimation

2007 ◽  
Vol 20 (3) ◽  
pp. 499-506
Author(s):  
Iskandar Karapetyan
Keyword(s):  
Positive Integer ◽  
Heuristic Algorithms ◽  
Clique Number ◽  
Directed Path ◽  
Channel Routing ◽  
Routing Problem ◽  
Thickness Estimation ◽  
Channel Thickness ◽  
Np Complete ◽  
Routing Method

Channel routing is an important phase of physical design of LSI and VLSI chips. The channel routing method was first proposed by Akihiro Hashimoto and James Stevens [1]. The method was extensively studied by many authors and applied to different technologies. At present there are known many effective heuristic algorithms for channel routing. A. LaPaugh [2] proved that the restrictive routing problem is NP-complete. In this paper we prove that for every positive integer k there is a restrictive channel C for which ?(C)>? (HG)+L(VG)+k, where ? (C) is the thickness of the channel, ?(HG) is clique number of the horizontal constraints graph HG and L(VG) is the length of the longest directed path in the vertical constraints graph VG.

Algorithms for Generating Random Channel Instances for Channel Routing Problem

2010 ◽  
Vol 1 (1) ◽  
pp. 106 ◽  
Author(s):  
Achira Pal ◽  
Tarak N. Mandal ◽  
Rajat K. Pal ◽  
Debojit Kundu ◽  
Alak K. Datta
Keyword(s):  
Channel Routing ◽  
Routing Problem

Generation of random channel specifications for channel routing problem

2008 ◽  
Author(s):  
Achira Pal ◽  
Tarak N. Mandal ◽  
Alak K. Datta ◽  
Debojit Kundu ◽  
Rajat K. Pal
Keyword(s):  
Channel Routing ◽  
Routing Problem

INTEGRATED CIRCUIT CHANNEL ROUTING USING A PARETO-OPTIMAL GENETIC ALGORITHM

2012 ◽  
Vol 21 (05) ◽  
pp. 1250041
Author(s):  
THEODORE W. MANIKAS
Keyword(s):  
Integrated Circuit ◽  
Routing Algorithm ◽  
Signal Propagation ◽  
Pareto Optimal ◽  
Signal Delay ◽  
Integrated Circuit Design ◽  
Channel Routing ◽  
Routing Problem ◽  
Propagation Delays ◽  
Optimal Approach

An important part of the integrated circuit design process is the channel routing stage, which determines how to interconnect components that are arranged in sets of rows. The channel routing problem has been shown to be NP-complete, thus this problem is often solved using genetic algorithms. The traditional objective for most channel routers is to minimize total area required to complete routing. However, another important objective is to minimize signal propagation delays in the circuit. This paper describes the development of a genetic channel routing algorithm that uses a Pareto-optimal approach to accommodate both objectives. When compared to the traditional channel routing approach, the new channel router produced layouts with decreased signal delay, while still minimizing routing area.

Sign in / Sign up

Export Citation Format

Share Document