Modeling semiconductor for simulating signal, power, and electromagnetic integrity

Semiconductor Modeling: For Simulating Signal, Power, and Electromagnetic Integrity 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.

Darren J. Carpenter, BT Exact

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

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