Mixed-signal SOC verification using analog behavioral models

Qi Wang, Cadence Design Systems -August 21, 2012

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The era of “Internet everywhere” is creating a spectrum of applications targeted toward low-power and mixed-signal design, in segments ranging from health care to automotive to communications. Meanwhile, design challenges such as intellectual-property selection and integration as well as SOC- and system-level verification are spawning a whole new class of problems for EDA tools.

Mixed-signal design engineers face increasing difficulties in design and verification of complex mixed-signal SOCs. In a survey of mixed-signal design engineers during the 2011 Mixed-Signal Tech on Tour, a worldwide series presented by Cadence Design Systems Inc, the 561 respondents identified mixed-signal verification as a top customer challenge.

The performance of Spice simulation is prominent in the difficulties being reported (Figure 1). Analog Spice and Fast-Spice simulators are orders of magnitude slower than digital simulators and are slower still when compared with emulators and hardware accelerators. A June 2011 Design Automation Conference panel discussed the need for analog design and verification to become more like digital—that is, to become more structured and more top-down (Reference 1). Verification planning tools are required, and debug methodologies such as ABV (assertion-based verification), MDV (metric-driven verification), and UVM (universal verification methodology)-like self-checking test benches must be created for analog/mixed-signal.

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To tackle simulation-throughput issues, designers are turning to behavioral-modeling techniques, which can increase simulation speed. Such techniques include event-driven simulation based on Verilog-A, Verilog-AMS, and RNM (real-number modeling).

Analog behavioral models are typically written in Verilog-AMS, Verilog-A, VHDL-AMS, or SystemVerilog.

Verilog-A is a pure-analog subset of Verilog-AMS and is mainly used for detailed analog models for performance verification. The language is quite simple, but it is challenging to write a good behavioral model with Verilog-A that provides significant performance gains while retaining the right level of accuracy. The advantage of Verilog-A is the ability to use models in pure-analog simulations as well as in the mixed-signal environment. The models are too low-level, however, to enable efficient SOC-level verification of mixed-signal designs.

The RNM technique models electrical signals by representing them as real values. Provided that the modules are at a sufficiently high level of abstraction, the interfaces can be described by passing real numbers between blocks to represent the voltage, or current, signal being transferred. This is a powerful way to simulate complex systems rapidly. Traditionally, iterating to a solution involving feedback would require an analog solver (see sidebar, “Analog versus digital solvers”).

RNM is available in the Verilog-AMS, SystemVerilog, and VHDL-AMS languages. A commonly used RNM approach is the wreal data type in Verilog-AMS. RNM uses a discrete event solver—without an analog solver—and can be used to simulate mixed-signal systems at incredible speeds. It is primarily limited to modeling at a high enough level of abstraction that bidirectional analog interactions between blocks are not significant. In other words, typical RNM defines blocks in terms of input/output transfer characteristics, with no strong direct feedback present among the blocks. Logic can be modeled naturally in these languages, so RNM is also a good choice for systems with only a small amount of analog content.

Top-down or bottom-up

Designers use two principal methodologies based on the creation of behavioral models for mixed-signal design. In a top-down methodology, models are developed before the circuits are designed. The behavioral models can be simpler ones that are sufficient for functional verification at the system level. In a bottom-up methodology, the models are written to match an already implemented block for performance verification and usually result in a more accurate but slower-running model.

The creation of analog behavioral models can be challenging. Analog designers are in the best position to create such models because they are familiar with their own circuits. Many analog designers lack the programming skills and knowledge required to construct behavioral models, however, and few are familiar with Verilog or VHDL. Digital designers, conversely, have expertise with behavioral models but know less about analog circuits.

That dichotomy creates an opportunity for tool vendors to offer an automated or semi-automated solution for generating analog behavioral models. For example, automated, netlist-driven model-generation technologies can create a fairly accurate parametric behavioral model that considers PVT (process, voltage, and temperature) and loading variations for functional verification. Such an approach has shown some limited success on a subset of analog-circuit architectures under specific contexts, but there is still much work to be done to develop a general model-generation methodology with high accuracy that can be applied to any analog or mixed-signal design.

Creating behavioral models is only one part of the process of using those models in a mixed-signal verification flow. If the model and implementation do not match, the effort is worthless; worse, it can damage the entire design process. As a result, there is a need for a methodology to validate the accuracy of a behavioral model automatically against the corresponding design. The model also must be updated to keep it in sync with any changes made in the implementation.

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