Next:
1. Introduction
Up:
Dissertation
Previous:
Acknowledgement
Inhalt
1. Introduction
1.1 The SIESTA TCAD Environment
1.2 The Structure of this Work
2. Technology Computer Aided Design
2.1 Process Modeling
2.1.1 Topography Processing
2.1.2 Ion Implantation
2.1.3 Thermal Processing
2.1.4 Pseudo Process Models
2.2 Electrical Modeling
2.2.1 Device Simulation
2.2.2 Interconnect Analysis
2.3 Technology Characterization
2.3.1 Statistical Analysis
2.4 Process Optimization
2.4.1 Optimization Target
2.5 Calibration of Models
3. Modeling Components
3.1 Conventional TCAD
3.2 The Historical Perspective
3.2.1 The Data Level
3.2.2 Task Automation
3.3 SIESTA's Modeling Approach
3.3.1 Linear Sequences of Simulation Tools
3.3.2 Simulation Networks
3.3.3 Data Manipulation
3.3.4 TCAD Models
3.4 The Simulation-Flow-Model
3.4.1 The Simulation-Flow-Model's Description
3.4.2 The Tool-Flow
3.4.3 Mapping Tool Results to Output Ports
3.4.4 Auxiliary Symbols
3.5 The Network-Model
3.5.1 Model Reuse
3.5.2 Default Overloading
3.5.3 The Network-Model's Description
3.6 Auxiliary Models
3.6.1 The Arithmetic-Model
3.6.2 The Curve-Calculator-Model
3.6.3 The Curve-To-File-Model
3.6.4 The Curve-To-Vector-Model
3.6.5 The Merge-Vector-Model
3.6.6 The Copy-File-Model
4. SIESTA's TCAD Experiments
4.1 The Generic Experiment
4.2 Optimization Experiments
4.2.1 Global Optimization
4.2.2 A Levenberg-Marquardt Optimization Tool
4.2.3 SIESTA's Process Optimization Environment
4.3 Design of Experiments
4.4 Statistical Analysis
5. Building Simulation Models
5.1 Modeling Fabrication Processes
5.1.1 Controlling Simulation Tools
5.1.2 Capturing Simulation Results
5.1.3 Using Results of Preceding Tools
5.1.4 Lithography Masks
5.1.5 Using Heterogeneous Process Simulation Tools
5.2 Performing Device Simulation
5.2.1 Producing a Device Simulation Mesh
5.3 Short Flow Methodologies
5.4 Modeling Integrated Circuits
5.5 Evaluation of Simulation-Flow-Models
5.5.1 Split Checking
5.5.2 Result Management
5.5.3 Fault Tolerance
6. Parallel and Distributed Simulation
6.1 Parallel Computation
6.1.1 Bottom-Level Strategy
6.1.2 Top-Level Strategy
6.1.3 Summary
6.2 Distributed Computing
6.2.1 Workload Distribution
6.2.2 Robustness
6.2.3 Load Polling
6.2.4 Host Selection
6.3 Performance Estimation
6.4 User Interaction and Feedback
6.4.1 The Queue Manager GUI
6.4.2 Configuration of the Job Farming System
7. Implementation of the SIESTA TCAD Environment
7.1 Implementation Issues
7.2 The Modular Architecture
7.2.1 Batch Operation
7.2.2 Module Initialization and Termination
7.2.3 Module Definition
7.3 Persistent Storage of Objects
7.3.1 Dynamical Instantiation
7.3.2 Database of Persistent Objects
7.3.3 Usage of Persistent Objects
7.4 Graphical User Interface Modeling
7.4.1 Component Abstraction and Reuse
7.4.2 Interface Descriptions
7.4.3 Maintenance Aspects
7.5 The Job Farming Module
7.5.1 Tasks
7.5.2 Virtual Hosts
7.5.3 Load Balancing
7.6 The Curve Module
7.6.1 The Curve Viewer
8. Technology Optimization
8.1 An Optimization Scenario
8.1.1 Modeling the Fabrication Process
8.1.2 Device Characterization
8.1.3 Evaluation of the Quality Metric
8.1.4 Configuring the Optimization Experiment
8.2 Optimization Results
8.2.1 Computation Efficiency
8.2.2 System Scalability
9. Inverse Modeling with SIESTA
9.1 A General Purpose Inverse Modeling Setup
9.1.1 The TCAD Experiment
9.1.2 Evaluation of a Model's Match
9.2 Evolution of Simulation Models
9.3 Inverse Modeling of Doping Profiles
9.3.1 The Inverse Modeling Problem
9.3.2 Modeling the Doping Profile
9.3.3 Deriving a Metric for the Match
9.3.4 Handling Multiple Devices and Bulk Biases
9.3.5 Running the Inverse Modeling Procedure
9.3.6 Simulation Results
10. Conclusion
10.1 User Acceptance
10.2 Robustness
10.3 The Modular Implementation
10.4 Further Research
10.4.1 Analysis Capabilities
10.4.2 Web Enabled TCAD
A. The VLISP object system
A1. The Definition of a Class
B. Notifications
C. The CRV Data Format
Literatur
To Eva
Rudi Strasser
1999-05-27
