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9780387241593

Semiconductor Modeling

by ; ;
  • ISBN13:

    9780387241593

  • ISBN10:

    0387241590

  • Edition: CD
  • Format: Hardcover
  • Copyright: 2006-11-30
  • Publisher: Springer Verlag
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Supplemental Materials

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Summary

This book assists engineers - both recent graduates and working product designers - in designing high-speed circuits. The authors apply circuit theory, circuit simulation tools, and practical experience to help the engineer understand semiconductor modeling as applied to high-speed digital designs. The emphasis is on semiconductor modeling, with PCB transmission line effects, equipment enclosure effects, and other modeling issues discussed as needed. The text addresses many practical considerations, including process variation, model accuracy, validation and verification, signal integrity, and design flow. Readers will benefit from its survey of modeling for semiconductors, packages, and interconnects, along with usable advice on how to get complex, high-speed prototypes to work on the first try.Highlights include:- Presents a very complete and well-balanced treatment of modeling of semiconductors, packages, and interconnects. Facilitates reader comprehension of the whole field of high-speed modeling, including digital and RF circuits.- Combines practical modeling techniques with the latest EDA tools for simulation and successful high-speed digital design. Facilitates resolution of practical, every-day problems.- Presents modeling from its historical roots to current state of the art. Facilitates keeping abreast of the latest modeling developments as they continue to unfold.- Includes a CD-ROM with modeling software and additional model examples.

Table of Contents

Preface xv
Acknowledgments xix
PART 1: INTRODUCTION 1(46)
1 How the Workplace Supports Successful Design
3(12)
1.1 High-Speed Digital Design Is Challenging
3(3)
1.2 Needs for Technical Specialization
6(1)
1.3 The Role of Processes and Procedures
7(1)
1.4 Using Judgment When Making Design Tradeoffs
8(1)
1.5 HSDD Needs the Help of EDA Tools
9(1)
1.6 HSDD Needs a Team That Extends Beyond the Company
9(1)
1.7 HSDD Team Members Often Have Their Own Agendas
10(1)
1.8 HSDD Simulations Performed in the Workplace
11(1)
1.9 Modeling and Simulation Versus Prototype and Debug
12(1)
1.10 Ten Tips for Modeling and Simulation
13(1)
1.11 Summary
13(2)
2 Introduction to Modeling Concepts
15(32)
2.1 Modeling and Simulation for All Scales of System Size
15(1)
2.2 Communicating Across Specialties
15(1)
2.3 What Is a Model?
16(2)
2.4 What Is a System?
18(2)
2.5 Needs for Model Accuracy Change as a Design Progresses
20(2)
2.6 There Are Many Kinds of Models and Simulations
22(1)
2.7 Modeling and Simulation for Systems
23(1)
2.8 Bottom-Up and Top-Down Design
24(3)
2.9 Analog Issues in Digital Design
27(7)
2.10 Noise Modeling on Electrical Signals
34(2)
2.11 Additional Design Issues to Model and Simulate
36(5)
2.12 Using EDA Tools for Semiconductors
41(2)
2.13 Using EDA Tools for Board Interconnections
43(2)
2.14 Looking Ahead in the Book
45(1)
2.15 Summary
45(2)
PART 2: GENERATING MODELS 47(104)
3 Model Properties Derived from Device Physics Theory
49(46)
3.1 Introduction
49(1)
3.2 Why Deep Sub-Micron Technology Is Complex
50(2)
3.3 Models Extracted from Semiconductor Design Theory
52(1)
3.4 Example of the BJT Process
53(1)
3.5 How BJT and FET Construction Affect Their Operation
54(11)
3.6 Calculating Device Physics Properties
65(6)
3.7 Examples of Computing Electrical Properties from Structure
71(4)
3.8 Examples of SPICE Models and Parameters
75(15)
3.9 Modeling Packaging Interconnections
90(3)
3.10 Summary
93(2)
4 Measuring Model Properties in the Laboratory
95(38)
4.1 Introduction to Model Measurements
95(2)
4.2 Matrix Models
97(6)
4.3 Scattering-Parameter Models
103(3)
4.4 SPICE Models
106(8)
4.5 IBIS Models
114(12)
4.6 Web Sites for IBIS Visual Editors and Other Tools
126(1)
4.7 TDR/TDT - VNA Measurements
126(1)
4.8 RLGC Matrixes
127(3)
4.9 Field Solver RLGC Extraction for ICs
130(1)
4.10 What is Model Synthesis?
130(1)
4.11 Test Equipment Providers
130(1)
4.12 Software for Test Equipment Control
131(1)
4.13 Summary
132(1)
5 Using Statistical Data to Characterize Component Populations
133(18)
5.1 Why Process Variation Is Important
133(1)
5.2 Achieving Process Control with Population Statistics
133(1)
5.3 Basics of Population Statistics
134(10)
5.4 Characterization for Six-Sigma Quality
144(5)
5.5 Six-Sigma Quality for Modeling and Design
149(1)
5.6 Summary
150(1)
PART 3: SELECTING COMPONENTS AND THEIR MODELS 151(108)
6 Using Selection Guides to Compare and Contrast Components
153(16)
6.1 Tools for Making Component Choices
153(2)
6.2 Team Members Use of Selection Guides
155(1)
6.3 Selection Guide Examples
156(5)
6.4 Selection Guides Help Component Standardization
161(1)
6.5 Simulation as a Selection Guide
161(5)
6.6 Right-Thinking
166(1)
6.7 Summary
167(2)
7 Using Data Sheets to Compare and Contrast Components
169(30)
7.1 Data Sheets as Product Descriptions
169(4)
7.2 Are Data Sheets Accurate and Complete?
173(2)
7.3 Selecting a Component That Is Fit for Use
175(1)
7.4 Using Data Sheets to Begin the Selection Process
176(2)
7.5 Construction Characteristics of Amplifiers and Switches
178(1)
7.6 Using Beta to Explain Device Tradeoffs
179(3)
7.7 Comparing Five BJTs to Illustrate Making a Selection
182(13)
7.8 Process for Making Tradeoffs
195(2)
7.9 Additional Choices for Picking a Component
197(1)
7.10 Thoughts About the Physical Design Examples
197(1)
7.11 Summary
198(1)
8 Selecting the Best Model for a Simulation
199(44)
8.1 From Component Choice to Model Choice
199(1)
8.2 Questions That Modeling and Simulation Can Answer
200(1)
8.3 Types of Models
201(1)
8.4 Using Symbols and Schematics to Represent Models
202(3)
8.5 Major Types of Models
205(6)
8.6 Compare Models by Simulation Performance
211(10)
8.7 Additional Model Comparisons
221(2)
8.8 Recommendations for Modeling
223(4)
8.9 Converting a Model to Another Type of Model
227(7)
8.10 Transform Models for Systems
234(7)
8.11 Summary
241(2)
9 Modeling and Simulation in the Design Process Flow
243(16)
9.1 Simulation in the Design Process
243(1)
9.2 A Typical Design Flow
244(4)
9.3 Strategy of Modeling and Simulation in Design
248(1)
9.4 Acquiring IBIS Models: An Overview
249(8)
9.5 Summary
257(2)
PART 4: ABOUT THE IBIS MODEL 259(166)
10 Key Concepts of the IBIS Specification
261(54)
10.1 Introduction
261(3)
10.2 IBIS Specification
264(19)
10.3 Sample IBIS Data File
283(11)
10.4 Parsing and Checking IBIS Data Files
294(3)
10.5 Schematic of a Basic IBIS Model
297(4)
10.6 How IBIS Circuit Modeling Methodology Is Used
301(8)
10.7 IBIS Test Circuits
309(1)
10.8 ISO 9000 Process Documentation for IBIS Models
310(4)
10.9 Summary
314(1)
11 Using IBIS Models in What-If Simulations
315(46)
11.1 A New Method of Design and Development
315(1)
11.2 Virtual Experiments
316(1)
11.3 Virtual Experiment Techniques
316(1)
11.4 Propagation Delay in High-Speed Nets
317(1)
11.5 Why We Use the IBIS Model
318(2)
11.6 Data Used in Experiments
320(2)
11.7 Experiment 1: Output Drive Capabity Versus Load
322(5)
11.8 Experiment 2: C_comp Loading
327(5)
11.9 All-Important Zo: Algorithms and Field Solvers
332(1)
11.10 Experiment 3: Edge Rate of a Driver and Reflections
333(3)
11.11 Experiment 4: Using V-T Data Versus a Ramp
336(10)
11.12 Experiment 5: Parasitics and Packaging Effects
346(3)
11.13 Experiment 6: Environmental and Population Variables
349(3)
11.14 Other Considerations: Timing and Noise Margin Issues
352(4)
11.15 Experiment 7: Vol from Simulation Versus Data Sheet
356(2)
11.16 How IBIS Handles Simulator Issues
358(1)
11.17 Summary
359(2)
12 Fixing Errors and Omissions in IBIS Models
361(34)
12.1 IBIS Model Validation Steps
361(1)
12.2 Process and Product Improvement Steps
362(1)
12.3 Step 1: Detect and Acknowledge the Quality Problem
363(1)
12.4 Step 2: Diagnose the Problem's Root Cause
364(2)
12.5 Step 3: Design a Fix Based on Root Cause
366(4)
12.6 Step 4: Verify the Fix
370(2)
12.7 Step 5: Archive Corrected Models
372(1)
12.8 Beyond Parsers and Checklists: Simulations and Reality Checking
372(2)
12.9 Tools Provided by the IBIS Committee
374(8)
12.10 IBIS Common Errors Checklist and Correction Procedures
382(4)
12.11 3Com's ISO 9000 Process for IBIS Models
386(5)
12.12 IBIS Model Acceptance and Legitimacy
391(3)
12.13 Summary
394(1)
13 Using EDA Tools to Create and Validate IBIS Models from SPICE
395(30)
13.1 Introduction
395(1)
13.2 I/O Buffer Example
396(3)
13.3 SPICE-to-IBIS Conversion Methodology
399(15)
13.4 Modeling Passive Interconnections in IBIS
414(1)
13.5 IBIS Model Validation
415(7)
13.6 Summary
422(3)
PART 5: MANAGING MODELS 425(52)
14 Sources of IBIS Models
427(26)
14.1 Model Needs Change as a Product is Developed
427(1)
14.2 List of IBIS Model Sources
428(2)
14.3 Using Default Models to Get Started
430(1)
14.4 Using the Company's Model Library
430(1)
14.5 Using the EDA Tool Provider's Model Library
430(1)
14.6 Searching the Web for the Supplier's Model
431(3)
14.7 Requesting Models Directly from the Supplier
434(2)
14.8 Purchasing a Commercial Third-Party Model Library
436(1)
14.9 Using Models Adapted from Other Models
437(3)
14.10 Review
440(1)
14.11 Purchasing Custom Models from a Third-Party
441(1)
14.12 Converting SPICE Models to IBIS Models
441(1)
14.13 Using a Supplier's Preliminary Models
441(9)
14.14 Asking SI-List and IBIS E-mail Reflectors for Help
450(1)
14.15 Modeling Tools on the IBIS Website
451(1)
14.16 Summary
452(1)
15 Working with the Model Library
453(24)
15.1 The Best Way to Manage Models
453(5)
15.2 Component Standardization and Library Management
458(12)
15.3 Storing and Retrieving Model Files
470(3)
15.4 Assigning Models to Components in EDA Simulators
473(3)
15.5 Flexibility in Model Choices at Run Time
476(1)
15.6 Summary
476(1)
PART 6: MODEL ACCURACY AND VERIFICATION 477(94)
16 Methodology for Verifying Models
479(32)
16.1 Overview of Model Verification
479(2)
16.2 Model Verification Methodology
481(8)
16.3 Verifying SPICE Models
489(8)
16.4 Verifying PDS Models
497(6)
16.5 Verifying IBIS Models
503(5)
16.6 Verifying Other Model Types
508(2)
16.7 Summary
510(1)
17 Verifying Model Accuracy by Using Laboratory Measurements
511(34)
17.1 Introduction
511(1)
17.2 Instrumentation Loading as a Source of Errors
512(5)
17.3 Other Test Setup Errors
517(2)
17.4 Signal Noise as a Source of Errors
519(1)
17.5 Measurement Definitions and Terms as a Source of Errors
520(2)
17.6 Two Ways to Correlate Models with Measurements
522(1)
17.7 Involving Production in Verification
523(1)
17.8 An EMI/EMC Example
523(1)
17.9 Correlating Unit-by-Unit Model Measurements
524(1)
17.10 Statistical Envelope Correlation
525(1)
17.11 Signal Integrity and Correlation
526(1)
17.12 Waveform Correlation
527(3)
17.13 Computational Electromagnetics and the Feature Selective Validation Method
530(4)
17.14 IBIS Golden Waveforms
534(1)
17.15 How Unexpected Errors Led to an Advance in Modeling
535(6)
17.16 Recommended Verification Strategy
541(3)
17.17 Summary
544(1)
18 Balancing Accuracy Against Practicality When Correlating Simulation Results
545(10)
18.1 Establishing Absolute Accuracy Is Difficult
545(2)
18.2 Is a Model Accurate Enough to Be Usable?
547(1)
18.3 Model Accuracy Definitions
547(1)
18.4 Confidence Limits in Measurements and Simulations
548(1)
18.5 How Much to Guard-Band Design Simulation?
549(1)
18.6 Differences in Accuracy, Dispersion, and Precision for Simulation and Measurement
550(1)
18.7 Model Limitations
551(1)
18.8 Standardization and the Compact Model Council
551(3)
18.9 Summary
554(1)
19 Deriving an Equation-Based Model from a Macromodel
555(16)
19.1 A "New" RF Design Challenge
555(1)
19.2 Background
555(1)
19.3 Applying the RF Example to High-Speed Digital Circuits
556(2)
19.4 Predicted and Measured Results
558(1)
19.5 Reverse Isolation Analyzed
559(7)
19.6 Optimizing Single-Stage Reverse Isolation
566(1)
19.7 Combining Stages for Power Isolation
567(2)
19.8 Calculations Versus Measurements
569(1)
19.9 Construction and Test Techniques
569(1)
19.10 Summary
570(1)
PART 7: FUTURE DIRECTIONS IN MODELING 571(134)
20 The Challenge to IBIS
573(58)
20.1 Emerging Simulation Requirements
573(3)
20.2 The Leading Contenders to Change IBIS
576(1)
20.3 Models in the Context of Simplification
577(1)
20.4 Physical Modeling
578(2)
20.5 Behavioral Modeling
580(8)
20.6 Developing a Macromodel from the Behavioral Model
588(4)
20.7 Developing a SPICE Macromodel from a Physical Model
592(16)
20.8 Limitations in Models Due to Simplification
608(2)
20.9 AMS Modeling Simplified
610(8)
20.10 Limitations Because of Parameter Variation
618(3)
20.11 Limitations of Deterministic Modeling and Design
621(8)
20.12 Summary
629(2)
21 Feedback to the Model Provider Improves Model Accuracy
631(10)
21.1 Continuing Need for Better Models
631(1)
21.2 How Far We Have Come
632(1)
21.3 Four-Step Universal Process for Improvement
633(1)
21.4 Specs That Swim Upstream: A New Approach
633(1)
21.5 Warnings About Doing What-If Model Simulations
634(1)
21.6 Selling the Idea of Better Models and Simulation
635(5)
21.7 Summary
640(1)
22 Future Trends in Modeling
641(42)
22.1 Bridges to the Future
641(1)
22.2 Challenge of HSDD
642(2)
22.3 How Design Methods Have Changed
644(1)
22.4 Attitudes in EMI/EMC about Modeling and Simulation
645(1)
22.5 High-Speed Design Is Becoming More Challenging
646(2)
22.6 Advantages of SPICE, S-Parameters, and IBIS
648(6)
22.7 Combining Models and EDA Tools to Design High-Speed Serial Busses
654(1)
22.8 IBIS: Past, Present, and Future Specification Additions
655(4)
22.9 Advantages of Pre-Layout Simulation for EMI/EMC
659(1)
22.10 Interconnection Design Applied to EMI/EMC
660(1)
22.11 Modeling for Power Integrity and EMI/EMC
661(10)
22.12 Computational Electromagnetics
671(5)
22.13 EDA Tool Supplier Survey
676(5)
22.14 Risk Management and the Limitations of Simulation
681(1)
22.15 Summary
681(2)
23 Using Probability: The Ultimate Future of Simulation Contributing author: Darren J. Carpenter, BT Exact
683(22)
23.1 Introduction
683(2)
23.2 Limitations of Deterministic Modeling and Design
685(2)
23.3 A New Approach: Probabilistic Modeling
687(1)
23.4 Complexity of the EMI Chain of Cause and Effect
688(1)
23.5 Risk Management Mathematics
689(3)
23.6 Identical Equipments Case
692(1)
23.7 Non-Identical Equipments Case
693(1)
23.8 Risk Assessment
693(1)
23.9 Distribution Examples
694(7)
23.10 Review of Probability Distributions
701(1)
23.11 Follow Up Simulation with Product Assurance
702(1)
23.12 Summary
703(2)
PART 8: GLOSSARY, BIBLIOGRAPHY, INDEX, AND CD-ROM 705
Glossary
707(26)
Bibliography
733(12)
Index
745
Using the Companion CD-ROM

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