Title: Semiconductor Modeling
for Simulating Signal, Power, and Electromagnetic Integrity
Authors: Roy G. Leventhal and Lynne Green, with
contributing author Darren J. Carpenter
Publisher: Springer
ISBN: 0-387-24159-0
This
book of 747 pages was interesting reading for me. I was expecting
highly mathematical and detailed modeling on the physics of semiconductor
devices, but was pleasantly surprised. The text is addressed mainly
to design engineers who need a broad view of semiconductor modeling,
especially in high-speed circuit boards. The main approach of
this book is not on the physics but on the use of simulation to
help solve practical problems. The book is about design ideas
and information sources to help implement those ideas. It is more
about how to properly apply CAD tools, how to work with suppliers,
design concepts, and processes to enable your design. The book
relates to EMC/EMI because it is basically tailored to high-speed
design in which signal integrity is an issue. I highly recommend
this book to those EMC/EMI engineers interested in modeling.
The book is organized into seven areas distributed among twenty
three chapters. The areas are: 1) where models and simulation
fit into product development, 2) generating 2-port, scattering
parameters, SPICE, and IBIS models, 3) selecting components and
their models, 4) about the IBIS models for simulations, 5) managing
IBIS models for simulation, 6) checking and verifying IBIS models,
and 7) the future of IBIS and related modeling techniques. There
are 12 appendices and the book comes with a CD ROM that teaches
users how to extract models and simulate with them plus a lot
more information of interest. Many specialists have contributed
technical material and reviewed the resulting content; therefore,
the book was very well researched.
How do a group of individuals from a company guarantee a successful
design? This is the topic of chapter 1. Management must provide
engineers with good EDA tools and a supportive company structure.
The chapter provides tips for modeling and simulation and sources
of good judgment when contemplating design objectives. Chapter
2 discusses modeling concepts with EDA tools in general terms.
The chapter introduces modeling for simulation and discuses top-down
and bottom-up concepts, sources of noise on digital signals, and
limitations of modeling. There are some rules of interest for
judging the model’s usefulness and integrity.
The second area is about generating models. Chapter 3 covers the
usage of basic physics to extract model parameters for modeling
and simulation. Discrete semiconductor types are used as examples
in the discussions of the link between device design and model
parameters. Modeling tools can be used to extract circuit model
properties from the structure, material, and electrical properties
of semiconductors. One tool discussed is TCAD, which provides
such a link between semiconductor device design and the electrical
characteristics represented by models of these devices. The chapter
ends with how to get information on the modeling of packaging
interconnects for EMI purposes. If you want to learn how to measure
your own semiconductor parameters, then chapter 4 is for you;
it discusses how to do this with test instruments. Sometimes you
want to measure model parameters to verify and validate models.
Also, some SPICE model parameters cannot be derived from device
modeling, so you have to measure them. It is interesting to know
that most published device models, including behavioral models,
are derived from a SPICE model, rather than from measurements;
yet the SPICE model may contain errors due to wrong assumptions
and as we use these models the error propagates to other derived
models. The chapter introduces how to measure parameters for 2-port
matrix, scattering parameters, SPICE, and IBIS models. Chapter
5 introduces some statistical control processes to examine how
parameters can spread in devices and how these parameters spreads
can affect simulations.
The third area deals with selecting components and their models.
Chapter 6 is about making design tradeoff choices among component
properties and the chapter devotes a few pages to the usage of
different types of selection guides to compare and contrast components.
It also discusses how the selection guides should be used by different
types of designs. Examples are discussed, including an example
where the use of simulations was required in order to make final
selections. An extension of this work is taken to chapter 7 concerning
the usage of data sheets to compare and contrast components. Using
the example of data sheets, this chapter illustrates making design
tradeoffs based on analog, high frequency, and driver impedance
behavior. In high frequency devices the analog behavior of I/O
devices is important. Chapter 8 discusses the advantages and disadvantages
of different types of models in order to select the best model
for your simulations. Once you select the best components for
your design (chapters 6 and 7), you need to choose the best model
to analyze how that device will behave in the circuit. Each model
has its advantages and disadvantages for the task at hand. The
major types are SPICE, IBIS, and S-parameters. SPICE models are
complex and useful for addressing physical effects. S-parameter
models can handle high frequency effects but do not model time
domain switching well. IBIS provides a good balance simulation
between complexity and speed, and it is the best kind of model
to use in the majority of PCB-level simulations. However, in EMI/EMC,
the complexity increases and you need to address, and even develop,
other types of models in high-speed design. You can often tinker
with an existing model to be converted to another model that will
be more useful to you. The process of finding, making, and buying
IBIS models must start as early as possible, and this is discussed
in chapter 9. Early simulations can address critical circuits
while later simulations can be more accurate and should cover
all the rest.
The fourth area of this book addresses the IBIS model. Chapter
10 addresses key concepts of the IBIS specification. The IBIS
specification provides strict rules (large files, detailed and
complex) for modeling data exchange in order to ensure that model
data files are software neutral. The IBIS model data file is the
most practical model to use for most high-speed simulations. It
offers the best compromise between simulation speed and model
complexity. This compromise is done by ignoring the internal behavior
of the drivers’ circuitry and just modeling the behavior
of the terminals. It is important to have a good process and good
tools for validating IBIS data model files. Two such tools discussed
in the chapter are the IBIS committee’s golden parser and
the quality checklist. What if you want to change things in your
IBIS files? What happens when we change model parameters (as in
virtual experiments)? This is the subject of chapter 11. This
chapter describes seven virtual experiments in which parameter
values are changed and the effects of those changes are simulated.
The simulated results are then compared to circuit theory to ensure
that they are consistent. What if there are errors and omissions
in the IBIS models? Yes, it does happen and chapter 12 discusses
the ability to validate, fix and create models, all of which are
essential for the engineer. The IBIS specification will grow even
larger and more complex as it incorporates better modeling of
complex I/O at higher frequencies. Therefore, there are bound
to be mistakes. The engineer must have the skills to fix the models
for his/her simulations. It takes time and effort to learn how
to create, validate, and fix IBIS files correctly. Thanks to the
usage of some EDA tools (e.g. Model Integrity from Cadence), the
process of creating and validating IBIS models from SPICE can
be accomplished. Model validation checks both model syntax and
model data and this is discussed in chapter 13. The final step
when using the model in a simulation is to check for unexpected
interactions between the model and the simulator. The validation
methodologies described in this chapter are applicable to any
model; it can be applied to both transistor-level models and behavioral
models. A behavioral model can be expressed in many ways, including
SPICE controlled sources, IBIS tables, VHDL, and Verilog. The
validation makes sure the model data is correct, and that it produces
the expected simulation results.
The fifth area deals with managing models. Chapter 14 discusses
how to get IBIS models. IBIS models are available from a variety
of sources, but it takes perseverance to find and prepare models
that are good enough to use. A lot of the effort in simulation
deals with obtaining, fixing, creating, and archiving models.
Engineers need to understand the sources and strategies for obtaining
IBIS models in sufficient quality to meet their needs. Engineers
also need to know how to create and validate IBIS models when
none are available. Sources of IBIS models include semiconductor
suppliers, third-party modeling services, and conventional SPICE
models. Another source is to adapt models already in existence.
Hopefully, you are not alone in developing models and your workplace
has a good stock of model libraries. Chapter 15 deals with working
with model libraries. A well-managed library helps conserve and
leverage engineering resources. Standardization of commodity components
reduces the proliferation of unnecessary parts and data and is
a philosophy that should be employed in managing the library.
The company’s library serves as the central database for
all component-related information. If the model files are part
of this component library, the component library can also provide
for model storage, retrieval, and use. A well-managed library
is a good investment for the company.
The sixth area deals with model accuracy and verification. Chapter
16 deals with verification methodology for models. Verification
compares model simulation results against hardware test data,
making model verification the final step in modeling. The verification
methodology described in this chapter can be used for SPICE, IBIS,
and other model types. Verification can be done against a single
model (stand-alone) or against a model within a design. Chapter
17 covers the verification of model accuracy by using laboratory
measurements. Normally you can first obtain physical units, measure
their model parameters, simulate their behavior with measured
parameters, build circuits with the measured units, measure the
circuits in the laboratory, and correlate the measurements with
the simulation. A more efficient alternative is to model and simulate
a population of devices, assemble a representative sample of the
devices into multiple test circuits, measure the population of
test circuits, and then compare it to the population of simulation
results. Since all models contain simplifications and approximations
of what they represent, engineers must exercise good judgment
for deciding when a specific model is fit for use; this is discussed
in chapter 18. Chapter 19 shows an example of behavioral modeling
for an RF amplifier.
The seventh area deals with the future direction of modeling.
Chapter 20 is the largest chapter in the book and it addresses
the challenges to IBIS. Two emerging approaches to modeling complex
I/O are macromodels and AMS (analog mixed signal) equation based
model languages. These approaches allow IBIS to keep up with circuit
design evaluation of complex I/O. After a decade of dominance
in simulating I/O, IBIS is losing ground because of its limitations
in simulating complex programmable I/O. Possible solutions include
using physical models (SPICE), behavioral models, macromodels,
and the AMS modeling languages. The leading contender to solving
the complex I/O modeling issues is the AMS modeling language.
This chapter briefly reviews several modeling methods as they
apply to model fabrication. Communication between semiconductor
suppliers and OEM users should be interactive. Today, cutting
edge ICs, net topology, routing, and termination are developed
by a team of logic design engineers, signal integrity engineers,
and PCB designers. This is discussed in chapter 21. Chapter 22
discusses the future trends in modeling. Rapid advances in technology
have opened new opportunities and challenges in modeling and simulation.
Signal integrity, power integrity, EMI/EMC, and simulation are
becoming more necessary and more challenging. New ideas being
applied to high-speed digital design include the use of macro
modeling, VHDL-AMS, and S-parameters models. Advances in EDA tools
and simulation models are helping engineers meet new challenges.
Finally, chapter 23 discusses the usage of probability distributions
in simulations. This is my favorite chapter because it happens
to address an area that interests me and in which I have only
had partial success. The view reached is of a discipline very
different from that of today. This chapter presents modeling as
a deductive exercise in the mapping of a parameter space. Each
single valued model parameter is replaced by a statistical parameter
that exists within a physical range with a defined probability
function. To be economical, most designs must be produced within
the probability of particular combinations of variables occurring
at any one time. An absolute worst-case combination of variables
is usually unlikely. For the target quantity, simulation yields
both a physical range and a confidence level by mapping of the
model parameter space. Examples are presented for very simple
problems.
In summary, this book is good reading without much math. It is
more about the big picture in modeling. EMC