Constraint Propagation for Analog and Mixed-Signal Integrated Circuit Design
Zusammenfassung
While the design of digital integrated circuits (ICs) is largely automated, the design of analog/ mixed-signal (AMS) ICs is still dominated by manual tasks. One of the biggest obstacles to further automation is the large number of constraints that have to be taken into account during AMS IC design. They are derived both from the specifcation and during the actual design process and must be fulflled before production of the IC can begin. The aim of this work is to present our fndings regarding the formalization of constraints and their propagation within the design hierarchy in order to make them visible and verifable in all relevant cells. Constraints are integrated into the AMS IC design process so that they can be considered at all stages of the design. Our research enables the integration and consideration of constraints in all types of design tools—not only for AMS IC design, but after generalization for any design process.
Contents
Abbreviations
VIII
Selected Symbols
X
...
Schlagworte
- Kapitel Ausklappen | EinklappenSeiten
- I–XIV
- 1–9 1 Introduction 1–9
- 1.1 Design of Analog and Mixed-Signal Integrated Circuits
- 1.2 Constraints and Constraint-driven Design
- 10–17 2 State of the Art 10–17
- 2.1 Constraint-driven Design
- 2.1.1 Constraint Modeling
- 2.1.2 Constraint Classification
- 2.1.3 Constraint Derivation
- 2.1.4 Constraint Propagation
- 2.2 Design Databases
- 18–20 3 Research Objectives 18–20
- 21–40 4 Constraints and Constraint Types 21–40
- 4.1 Design Hierarchy
- 4.2 Constraint Definition
- 4.2.1 Constraint Context
- 4.2.2 Constraint Function
- 4.2.3 Target Parameters
- 4.2.4 Constraint Members
- 4.3 Constraint Types
- 4.3.1 Constraint Type Definition Using Constraint Function Sets
- 4.3.2 Constraint Type Definition Using Higher-Order Functions
- 4.3.3 Constraint Type Definition Using Expression Trees
- 4.4 Summary and Conclusions
- 41–90 5 Constraint Propagation 41–90
- 5.1 Generic Propagation Algorithm
- 5.2 Propagation Trees
- 5.3 Non-Propagating Parameters
- 5.4 Propagation Based on Instantiation
- 5.4.1 Top-Down Propagation
- 5.4.2 Bottom-Up Propagation
- 5.5 Propagation Based on Connectivity
- 5.5.1 Propagation Based on Logical Connectivity
- 5.5.2 Propagation Based on Physical Connectivity
- 5.5.3 Propagation Based on Logical and Physical Connectivity
- 5.6 Propagation Based on Spatial Adjacency
- 5.7 Constraint Verification and Budget Calculation
- 5.7.1 Calculation of Current Values
- 5.7.2 Constraint Verification
- 5.7.3 Budget Calculation
- 5.7.4 Budget Allocation
- 5.8 Discussion
- 5.9 Summary and Conclusions
- 91–102 6 Adaptive Data Model for Efficient Constraint Propagation 91–102
- 6.1 State of the Art
- 6.2 Overview
- 6.3 Library Organization
- 6.4 View Data Model
- 6.5 Constraint Data Model
- 6.6 Adaptive Model Extensions
- 6.6.1 Mandatory Data Model Extensions
- 6.6.2 Optional Data Model Extensions
- 6.6.3 Extension Selection
- 6.6.4 Constraint Removal
- 6.7 Summary and Conclusions
- 103–121 7 Implementation and Results 103–121
- 7.1 Data Model
- 7.1.1 Graph Database and its Design Tool Integration
- 7.1.2 Data Export and Synchronization
- 7.1.3 Examples
- 7.2 Design Example
- 7.3 Constraint Propagation
- 7.3.1 New Constraint Types
- 7.3.2 Propagation Tree Generation
- 7.3.3 Constraint Localization
- 7.3.4 Visualization of Propagation Trees
- 7.4 Summary and Conclusions
- 122–127 8 Research Summary, Conclusions, and Outlook 122–127
- 8.1 Research Summary and Conclusions
- 8.2 Research Outlook
- 128–131 Glossary 128–131
- 132–146 Bibliography 132–146
