A framework for fine-grain synthesis optimization of operational amplifiers

This thesis presents a cell-level framework for Operational Amplifiers Synthesis (OASYN) coupling both circuit design and layout. For circuit design, the tool applies a corner-driven optimization, accounting for on-chip performance variations. By exploring the process, voltage, and temperature variations space, the tool extracts design worst case solution. The tool undergoes sensitivity analysis along with Pareto-optimality to achieve required specifications. For layout phase, OASYN generates a DRC proved automated layout based on a sized circuit-level description. Morata et al. (1996) introduced an elegant representation of block placement called sequence pair for general floorplans (SP). Like TCG and BSG, but unlike O-tree, B*tree, and CBL, SP is P-admissible. Unlike SP, TCG supports incremental update during operation and keeps the information of the boundary modules as well as their relative positions in the representation. Block placement algorithms that are based on SP use heuristic optimization algorithms, e.g., simulated annealing where generation of large number of sequence pairs are required. Therefore a fast algorithm is needed to generate sequence pairs after each solution perturbation. The thesis presents a new simple and efficient O(n) runtime algorithm for fast realization of incremental update for cost evaluation. The algorithm integrates sequence pair and transitive closure graph advantages into TCG-S* a superior topology update scheme which facilitates the search for optimum desired floorplan. Experiments show that TCG-S* is better than existing works in terms of area utilization and convergence speed. Routing-aware placement is implemented in OASYN, handling symmetry constraints, e.g., interdigitization, common centroid, along with congestion elimination and the enhancement of placement routability

The multi-BSG: stochastic approach to an optimum packing of convex-rectilinear blocks

Abstract A oorplannar that can handle convex-rectilinear blocks is developed by enhancing the BSG-based packing algorithm. The ideas are in the introduction of (1) multi-rectangle representation of a block as a superpose of element-rectangles, (2) parametric-BSG as a generalization of the BSG, (3) multi-BSG which is an arrangement of plural BSG's o n a m ulti-layer, and (4) layer sharing condition of element-rectangles so that non-overlapping is discussed on each layer. A solution space of packings is dened as the set of packings generated by c hanging parametric-BSG and room assignments. It is guaranteed to contain an optimal packing if the BSG is not smaller than a certain size. A oorplan based on a simulated annealing was implemented. In experiments, it output highly compressed packings

A Massively Parallel 2D Rectangle Placement Method

Layout design is a frequently occurring process that oftencombines human and computer reasoning. Because of the combinatorialnature of the problem, solving even a small size input involves searchinga prohibitively large state space. An algorithm PEMS (Pseudo-exhaustiveEdge Minimizing Search) is proposed for approximating a 2D rectanglepacking variant of the problem. The proposed method is inspiredby MERA (Minimum Enclosing of Rectangle Area) [1] and MEGA(Minimum Enclosing Under Gravitational Attraction) [2], yet produceshigher quality solutions, in terms of final space utilization. To addressthe performance cost, a CUDA based acceleration algorithm is developedwith significant speedup

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

Bus-driven floorplanning.

Law Hoi Ying.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 101-106).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- VLSI Design Cycle --- p.2Chapter 1.2 --- Physical Design Cycle --- p.6Chapter 1.3 --- Floorplanning --- p.10Chapter 1.3.1 --- Floorplanning Objectives --- p.11Chapter 1.3.2 --- Common Approaches --- p.12Chapter 1.3.3 --- Interconnect-Driven Floorplanning --- p.14Chapter 1.4 --- Motivations and Contributions --- p.15Chapter 1.5 --- Organization of the Thesis --- p.17Chapter 2 --- Literature Review on 2D Floorplan Representations --- p.18Chapter 2.1 --- Types of Floorplans --- p.18Chapter 2.2 --- Floorplan Representations --- p.20Chapter 2.2.1 --- Slicing Floorplan --- p.21Chapter 2.2.2 --- Non-slicing Floorplan --- p.22Chapter 2.2.3 --- Mosaic Floorplan --- p.30Chapter 2.3 --- Summary --- p.35Chapter 3 --- Literature Review on 3D Floorplan Representations --- p.37Chapter 3.1 --- Introduction --- p.37Chapter 3.2 --- Problem Formulation --- p.38Chapter 3.3 --- Previous Work --- p.38Chapter 3.4 --- Summary --- p.42Chapter 4 --- Literature Review on Bus-Driven Floorplanning --- p.44Chapter 4.1 --- Problem Formulation --- p.44Chapter 4.2 --- Previous Work --- p.45Chapter 4.2.1 --- Abutment Constraint --- p.45Chapter 4.2.2 --- Alignment Constraint --- p.49Chapter 4.2.3 --- Bus-Driven Floorplanning --- p.52Chapter 4.3 --- Summary --- p.53Chapter 5 --- Multi-Bend Bus-Driven Floorplanning --- p.55Chapter 5.1 --- Introduction --- p.55Chapter 5.2 --- Problem Formulation --- p.56Chapter 5.3 --- Methodology --- p.57Chapter 5.3.1 --- Shape Validation --- p.58Chapter 5.3.2 --- Bus Ordering --- p.65Chapter 5.3.3 --- Floorplan Realization --- p.72Chapter 5.3.4 --- Simulated Annealing --- p.73Chapter 5.3.5 --- Soft Block Adjustment --- p.75Chapter 5.4 --- Experimental Results --- p.75Chapter 5.5 --- Summary --- p.77Chapter 6 --- Bus-Driven Floorplanning for 3D Chips --- p.80Chapter 6.1 --- Introduction --- p.80Chapter 6.2 --- Problem Formulation --- p.81Chapter 6.3 --- The Representation --- p.82Chapter 6.3.1 --- Overview --- p.82Chapter 6.3.2 --- Review of TCG --- p.83Chapter 6.3.3 --- Layered Transitive Closure Graph (LTCG) --- p.84Chapter 6.3.4 --- Aligning Blocks --- p.85Chapter 6.3.5 --- Solution Perturbation --- p.87Chapter 6.4 --- Simulated Annealing --- p.92Chapter 6.5 --- Soft Block Adjustment --- p.92Chapter 6.6 --- Experimental Results --- p.93Chapter 6.7 --- Summary --- p.94Chapter 6.8 --- Acknowledgement --- p.95Chapter 7 --- Conclusion --- p.99Bibliography --- p.10