Timing Influenced Force Directed Floorplanning

We represent a timing driven floorplanning program for general cell layouts. The approach used combines quality of force directed approach wit that of constraint graph approach. A floorplan solution is produced in two steps. First a timing and connectivity driven topological arrangement is obtained using a force directed approach. In the second step, the topoligical arrangement is trasnformed into a legal floorplan. The objective of the second step is to minimize the overall area of the floorplan. The floorplanner is validated with circuits of sizes varying from 7-125 block

Timing influenced force directed floorplanning

We present a timing driven floorplanning program for general cell layouts. The approach used combines quality of force directed approach with that of constraint graph approach. A floorplan solution is produced in two steps. First a timing and connectivity driven topological arrangement is obtained using a force directed approach. In the second step, the topological arrangement is transformed into a legal floorplan. The objective of the second step is to minimize the overall area of the floorplan. The floorplanner is validated with circuits of sizes varying from 7 to 125 block

Timing influenced force directed floorplanning

We present a timing driven floorplanning program for general cell layouts. The approach used combines quality of force directed approach with that of constraint graph approach. A floorplan solution is produced in two steps. First a timing and connectivity driven topological arrangement is obtained using a force directed approach. In the second step, the topological arrangement is transformed into a legal floorplan. The objective of the second step is to minimize the overall area of the floorplan. The floorplanner is validated with circuits of sizes varying from 7 to 125 block

Parallelization of Stochastic Evolution for Cell Placement

VLSI physical design and the problems related to it such as placement, channel routing, etc, carry inherent complexities that are best dealt with iterative heuristics. However the major drawback of these iterative heuristics has been the large runtime involved in reaching acceptable solutions especially when optimizing for multiple objectives. Among the acceleration techniques proposed, parallelization is one promising method. Distributed memory multiprocessor systems and shared memory multiprocessor systems have gained considerable attention in recent years of research. This idea of parallel computing has attracted both the researchers and manufacturers who are targeting to reduce the time to market. Our objective is to exploit the benefits of parallel computing for a time consuming placement problem in VLSI. Finding the best solution for the placement of n modules is a hard problem. Thus the enumerative search techniques, specially those which employ the brute force, are unaccepted for the circuits in which n (number of modules) is large. Constructive and Iterative heuristics play the key role in this scenario and hence are frequently used. We will use Stochastic Evolution for finding the optimal solution to the above mentioned placement problem where the major task in our objective will be the parallelization of Stochastic Evolution using different parallelization techniques and the comparison between these different parallelized versions based on the results achieved. The parallelization will be carried out using MPI (Message Passing Interface) on a distributed memory multiprocessor system and conclusion will be based on the results achieved that are expected to show speedup nearly equal to linear speedup when run over increasing number of processors

Tabu searchbased circuit optimization

Abstract In this paper we address the problem of optimizing mixed CMOS/BiCMOS circuits. The problem, formulated as a constrained combinatorial optimization problem is addressed using a tabu searchalgorith m. Initially a random approachis adopted for selecting among available solutions. Further, as an alternative competing solution the concepts of simulated evolution are applied to classical tabu search (CTS). This allows for a stochastic criterion for selecting among available solutions as compared to the random approach of CTS. Only gates on the critical sensitizable paths are considered for optimization. Such a strategy leads to sizeable circuit speed improvement with minimum increase in the overall circuit capacitance. Compared to earlier approaches, the presented techniques produce circuits with remarkable increase in speed (greater than 20%) for very small increase in overall circuit capacitance (less than 3%). r 2002 Elsevier Science Ltd. All rights reserved

Interconnect-driven floorplanning.

Sham Chiu Wing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.Includes bibliographical references (leaves 107-113).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivations --- p.1Chapter 1.2 --- Progress on the Problem --- p.2Chapter 1.3 --- Our Contributions --- p.3Chapter 1.4 --- Thesis Organization --- p.5Chapter 2 --- Preliminaries --- p.6Chapter 2.1 --- Introduction --- p.6Chapter 2.1.1 --- The Role of Floorplanning --- p.6Chapter 2.1.2 --- Wirelength Estimation --- p.7Chapter 2.1.3 --- Different Types of Floorplan --- p.8Chapter 2.2 --- Representations of Floorplan --- p.10Chapter 2.2.1 --- Polish Expressions --- p.10Chapter 2.2.2 --- Sequence Pair --- p.11Chapter 2.2.3 --- Bounded-Sliceline Grid (BSG) Structure --- p.13Chapter 2.2.4 --- O-Tree --- p.14Chapter 2.2.5 --- B*-Tree --- p.16Chapter 2.2.6 --- Corner Block List --- p.18Chapter 2.2.7 --- Twin Binary Tree --- p.19Chapter 2.2.8 --- Comparisons between Different Representations --- p.20Chapter 2.3 --- Algorithms of Floorplan Design --- p.20Chapter 2.3.1 --- Constraint Based Floorplanning --- p.21Chapter 2.3.2 --- Integer Programming Based Floorplanning --- p.21Chapter 2.3.3 --- Neural Learning Based Floorplanning --- p.22Chapter 2.3.4 --- Rectangular Dualization --- p.22Chapter 2.3.5 --- Simulated Annealing --- p.23Chapter 2.3.6 --- Genetic Algorithm --- p.23Chapter 2.4 --- Summary --- p.24Chapter 3 --- Literature Review on Interconnect-Driven Floorplanning --- p.25Chapter 3.1 --- Introduction --- p.25Chapter 3.2 --- Simulated Annealing Approach --- p.25Chapter 3.2.1 --- """Pepper - A Timing Driven Early Floorplanner""" --- p.25Chapter 3.2.2 --- """A Timing Driven Block Placer Based on Sequence Pair Model""" --- p.26Chapter 3.2.3 --- """Integrated Floorplanning and Interconnect Planning""" --- p.27Chapter 3.2.4 --- """Interconnect Driven Floorplanning with Fast Global Wiring Planning and Optimization""" --- p.27Chapter 3.3 --- Genetic Algorithm Approach --- p.28Chapter 3.3.1 --- "“Timing Influenced General-cell Genetic Floorplanning""" --- p.28Chapter 3.4 --- Force Directed Approach --- p.29Chapter 3.4.1 --- """Timing Influenced Force Directed Floorplanning""" --- p.29Chapter 3.5 --- Congestion Planning --- p.30Chapter 3.5.1 --- """On the Behavior of Congestion Minimization During Placement""" --- p.30Chapter 3.5.2 --- """Congestion Minimization During Placement""" --- p.31Chapter 3.5.3 --- "“Estimating Routing Congestion Using Probabilistic Anal- ysis""" --- p.31Chapter 3.6 --- Buffer Planning --- p.32Chapter 3.6.1 --- """Buffer Block Planning for Interconnect Driven Floor- planning""" --- p.32Chapter 3.6.2 --- """Routability Driven Repeater Block Planning for Interconnect- centric Floorplanning""" --- p.33Chapter 3.6.3 --- """Provably Good Global Buffering Using an Available Block Plan""" --- p.34Chapter 3.6.4 --- "“Planning Buffer Locations by Network Flows""" --- p.34Chapter 3.6.5 --- """A Practical Methodology for Early Buffer and Wire Re- source Allocation""" --- p.35Chapter 3.7 --- Summary --- p.36Chapter 4 --- Floorplanner with Fixed Buffer Planning [34] --- p.37Chapter 4.1 --- Introduction --- p.37Chapter 4.2 --- Overview of the Floorplanner --- p.38Chapter 4.3 --- Congestion Model --- p.38Chapter 4.3.1 --- Construction of Grid Structure --- p.39Chapter 4.3.2 --- Counting the Number of Routes at a Grid --- p.40Chapter 4.3.3 --- Buffer Location Computation --- p.41Chapter 4.3.4 --- Counting Routes with Blocked Grids --- p.42Chapter 4.3.5 --- Computing the Probability of Net Crossing --- p.43Chapter 4.4 --- Time Complexity --- p.44Chapter 4.5 --- Simulated Annealing --- p.45Chapter 4.6 --- Wirelength Estimation --- p.46Chapter 4.6.1 --- Center-to-center Estimation --- p.47Chapter 4.6.2 --- Corner-to-corner Estimation --- p.47Chapter 4.6.3 --- Intersection-to-intersection Estimation --- p.48Chapter 4.7 --- Multi-pin Nets Handling --- p.49Chapter 4.8 --- Experimental Results --- p.50Chapter 4.9 --- Summary --- p.51Chapter 5 --- Floorplanner with Flexible Buffer Planning [35] --- p.53Chapter 5.1 --- Introduction --- p.53Chapter 5.2 --- Overview of the Floorplanner --- p.54Chapter 5.3 --- Congestion Model --- p.55Chapter 5.3.1 --- Probabilistic Model with Variable Interval Buffer Inser- tion Constraint --- p.57Chapter 5.3.2 --- Time Complexity --- p.61Chapter 5.4 --- Buffer Planning --- p.62Chapter 5.4.1 --- Estimation of Buffer Usage --- p.62Chapter 5.4.2 --- Estimation of Buffer Resources --- p.69Chapter 5.5 --- Two-phases Simulated Annealing --- p.70Chapter 5.6 --- Wirelength Estimation --- p.72Chapter 5.7 --- Multi-pin Nets Handling --- p.73Chapter 5.8 --- Experimental Results --- p.73Chapter 5.9 --- Remarks --- p.76Chapter 5.10 --- Summary --- p.76Chapter 6 --- Global Router --- p.77Chapter 6.1 --- Introduction --- p.77Chapter 6.2 --- Overview of the Global Router --- p.77Chapter 6.3 --- Buffer Insertion Constraint and Congestion Constraint --- p.78Chapter 6.4 --- Multi-pin Nets Handling --- p.79Chapter 6.5 --- Routing Methodology --- p.79Chapter 6.6 --- Implementation --- p.80Chapter 6.7 --- Summary --- p.86Chapter 7 --- Interconnect-Driven Floorplanning by Alternative Packings --- p.87Chapter 7.1 --- Introduction --- p.87Chapter 7.2 --- Overview of the Method --- p.87Chapter 7.3 --- Searching Alternative Packings --- p.89Chapter 7.3.1 --- Rectangular Supermodules in Sequence Pair --- p.89Chapter 7.3.2 --- Finding rearrangable module sets --- p.90Chapter 7.3.3 --- Alternative Sequence Pairs --- p.94Chapter 7.4 --- Implementation --- p.97Chapter 7.4.1 --- Re-calculation of Interconnect Cost --- p.98Chapter 7.4.2 --- Cost Function --- p.101Chapter 7.4.3 --- Time Complexity --- p.101Chapter 7.5 --- Experimental Results --- p.101Chapter 7.6 --- Summary --- p.103Chapter 8 --- Conclusion --- p.105Bibliography --- p.10

Fixed-outline bus-driven floorplanning.

Jiang, Yan.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (p. 87-92).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Physical Design --- p.2Chapter 1.2 --- Floorplanning --- p.6Chapter 1.2.1 --- Floorplanning Objectives --- p.7Chapter 1.2.2 --- Common Approaches --- p.8Chapter 1.3 --- Motivations and Contributions --- p.14Chapter 1.4 --- Organization of the Thesis --- p.15Chapter 2 --- Literature Review on BDF --- p.17Chapter 2.1 --- Zero-Bend BDF --- p.17Chapter 2.1.1 --- BDF Using the Sequence-Pair Representation --- p.17Chapter 2.1.2 --- Using B*-Tree and Fast SA --- p.20Chapter 2.2 --- Two-Bend BDF --- p.22Chapter 2.3 --- TCG-Based Multi-Bend BDF --- p.25Chapter 2.3.1 --- Placement Constraints for Bus --- p.26Chapter 2.3.2 --- Bus Ordering --- p.28Chapter 2.4 --- Bus-Pin-Aware BDF --- p.30Chapter 2.5 --- Summary --- p.33Chapter 3 --- Fixed-Outline BDF --- p.35Chapter 3.1 --- Introduction --- p.35Chapter 3.2 --- Problem Formulation --- p.36Chapter 3.3 --- The Overview of Our Approach --- p.36Chapter 3.4 --- Partitioning --- p.37Chapter 3.4.1. --- The Overview of Partitioning --- p.38Chapter 3.4.2 --- Building a Hypergraph G --- p.39Chapter 3.5 --- Floorplaiining with Bus Routing --- p.43Chapter 3.5.1 --- Find Bus Routes --- p.43Chapter 3.5.2 --- Realization of Bus Routes --- p.48Chapter 3.5.3 --- Details of the Annealing Process --- p.50Chapter 3.6 --- Handle Fixed-Outline Constraints --- p.52Chapter 3.7 --- Bus Layout --- p.52Chapter 3.8 --- Experimental Results --- p.56Chapter 3.9 --- Summary --- p.61Chapter 4 --- Fixed-Outline BDF with L-shape bus --- p.63Chapter 4.1 --- Introduction --- p.63Chapter 4.2 --- Problem Formulation --- p.64Chapter 4.3 --- Our Approach --- p.65Chapter 4.3.1 --- Bus Routability Checking --- p.67Chapter 4.3.2 --- Details of the Annealing Process --- p.79Chapter 4.4 --- Experimental Results --- p.79Chapter 4.5 --- Summary --- p.82Chapter 5 --- Conclusion --- p.85Bibliography --- p.9

Scalability and interconnection issues in floorplan design and floorplan representations.

Yuen Wing-seung.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves [116]-[122]).Abstracts in English and Chinese.Abstract --- p.iAcknowledgments --- p.iiiList of Figures --- p.viiiList of Tables --- p.xiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivations and Aims --- p.1Chapter 1.2 --- Contributions --- p.3Chapter 1.3 --- Dissertation Overview --- p.4Chapter 2 --- Physical Design and Floorplanning in VLSI Circuits --- p.6Chapter 2.1 --- VLSI Design Flow --- p.6Chapter 2.2 --- Floorplan Design --- p.8Chapter 2.2.1 --- Problem Formulation --- p.9Chapter 2.2.2 --- Types of Floorplan --- p.10Chapter 3 --- Floorplanning Representations --- p.12Chapter 3.1 --- Polish Expression(PE) [WL86] --- p.12Chapter 3.2 --- Bounded-Sliceline-Grid(BSG) [NFMK96] --- p.14Chapter 3.3 --- Sequence Pair(SP) [MFNK95] --- p.17Chapter 3.4 --- O-tree(OT) [GCY99] --- p.19Chapter 3.5 --- B*-tree(BT) [CCWW00] --- p.21Chapter 3.6 --- Corner Block List(CBL) [HHC+00] --- p.22Chapter 4 --- Optimization Technique in Floorplan Design --- p.27Chapter 4.1 --- General Optimization Methods --- p.27Chapter 4.1.1 --- Simulated Annealing --- p.27Chapter 4.1.2 --- Genetic Algorithm --- p.29Chapter 4.1.3 --- Integer Programming Method --- p.31Chapter 4.2 --- Shape Optimization --- p.33Chapter 4.2.1 --- Shape Curve --- p.33Chapter 4.2.2 --- Lagrangian Relaxation --- p.34Chapter 5 --- Literature Review on Interconnect Driven Floorplanning --- p.37Chapter 5.1 --- Placement Constraint in Floorplan Design --- p.37Chapter 5.1.1 --- Boundary Constraints --- p.37Chapter 5.1.2 --- Pre-placed Constraints --- p.39Chapter 5.1.3 --- Range Constraints --- p.41Chapter 5.1.4 --- Symmetry Constraints --- p.42Chapter 5.2 --- Timing Analysis Method --- p.43Chapter 5.3 --- Buffer Block Planning and Congestion Control --- p.45Chapter 5.3.1 --- Buffer Block Planning --- p.45Chapter 5.3.2 --- Congestion Control --- p.50Chapter 6 --- Clustering Constraint in Floorplan Design --- p.53Chapter 6.1 --- Problem Definition --- p.53Chapter 6.2 --- Overview --- p.54Chapter 6.3 --- Locating Neighboring Modules --- p.56Chapter 6.4 --- Constraint Satisfaction --- p.62Chapter 6.5 --- Multi-clustering Extension --- p.64Chapter 6.6 --- Cost Function --- p.64Chapter 6.7 --- Experimental Results --- p.65Chapter 7 --- Interconnect Driven Multilevel Floorplanning Approach --- p.69Chapter 7.1 --- Multilevel Partitioning --- p.69Chapter 7.1.1 --- Coarsening Phase --- p.70Chapter 7.1.2 --- Refinement Phase --- p.70Chapter 7.2 --- Overview of Multilevel Floorplanner --- p.72Chapter 7.3 --- Clustering Phase --- p.73Chapter 7.3.1 --- Clustering Methods --- p.73Chapter 7.3.2 --- Area Ratio Constraints --- p.75Chapter 7.3.3 --- Clustering Velocity --- p.76Chapter 7.4 --- Refinement Phase --- p.77Chapter 7.4.1 --- Temperature Control --- p.79Chapter 7.4.2 --- Cost Function --- p.80Chapter 7.4.3 --- Handling Shape Flexibility --- p.80Chapter 7.5 --- Experimental Results --- p.81Chapter 7.5.1 --- Data Set Generation --- p.82Chapter 7.5.2 --- Temperature Control --- p.82Chapter 7.5.3 --- Packing Results --- p.83Chapter 8 --- Study of Non-slicing Floorplan Representations --- p.89Chapter 8.1 --- Analysis of Different Floorplan Representations --- p.89Chapter 8.1.1 --- Complexity --- p.90Chapter 8.1.2 --- Types of Floorplans --- p.92Chapter 8.2 --- T-junction Orientation Property --- p.97Chapter 8.3 --- Twin Binary Tree Representation for Mosaic Floorplan --- p.103Chapter 8.3.1 --- Previous work --- p.103Chapter 8.3.2 --- Twin Binary Tree Construction --- p.105Chapter 8.3.3 --- Floorplan Construction --- p.109Chapter 9 --- Conclusion --- p.114Chapter 9.1 --- Summary --- p.114Bibliography --- p.116Chapter A --- Clustering Constraint Data Set --- p.123Chapter A.1 --- ami33 --- p.123Chapter A.1.1 --- One cluster --- p.123Chapter A.1.2 --- Multi-cluster --- p.123Chapter A.2 --- ami49 --- p.124Chapter A.2.1 --- One cluster --- p.124Chapter A.2.2 --- Multi-cluster --- p.124Chapter A.3 --- playout --- p.124Chapter A.3.1 --- One cluster --- p.124Chapter A.3.2 --- Multi-cluster --- p.125Chapter B --- Multilevel Data Set --- p.126Chapter B.l --- data_100 --- p.126Chapter B.2 --- data_200 --- p.127Chapter B.3 --- data_300 --- p.129Chapter B.4 --- data_400 --- p.131Chapter B.5 --- data_500 --- p.13