Solido Design Automation Inc.

Shawn Rusaw

Trent Lorne McConaghy

Kristopher Breen

David Callele

Joel Cooper

Jeffrey Dyck

Charles Cazabon

Jiandong Ge

Jason Coutu

Amit Gupta

Samer Sallam

Anthony Arkles

Pat Drennan

Jiangdon Ge

Sean Cocks

A system and method to analyze analog, mixed-signal, and custom digital circuits. The system and method displays to a user characteristic values of a circuit and statistical uncertainty values of the characteristic values early in a sampling or characterization run of the circuit. The characteristic values and their statistical uncertainties are updated as the sampling or characterization run progresses. The user can halt the sampling or characterization run once a desired level of uncertainty is attained. The system can automatically halt the sampling or characterization run, once the statistical uncertainty lie within a pre-determined range.

On-the-fly improvement of certainty of statistical estimates in statistical design, with corresponding visual feedback

For application to analog, mixed-signal, and custom digital circuits, a system and method to do: global statistical optimization (GSO), global statistical characterization (GSC), global statistical design (GSD), and block-specific design. GSO can perform global yield optimization on hundreds of variables, with no simplifying assumptions. GSC can capture and display mappings from design variables to performance, across the whole design space. GSC can handle hundreds of design variables in a reasonable time frame, e.g., in less than a day, for a reasonable number of simulations, e.g., less than 100,000. GSC can capture design variable interactions and other possible nonlinearities, explicitly capture uncertainties, and intuitively display them. GSD can support the user's exploration of design-to-performance mappings with fast feedback, thoroughly capturing design variable interactions in the whole space, and allow for more efficiently created, more optimal designs. Block-specific design should make it simple to design small circuit blocks, in less time and with lower overhead than optimization through optimization.

Global statistical optimization, characterization, and design

A method and system for performing multi-objective optimization of a multi-parameter design having several variables and performance metrics. The optimization objectives include the performance values of surrogate models of the performance metrics and the uncertainty in the surrogate models. The uncertainty is always maximized while the performance metrics can be maximized or minimized in accordance with the definitions of the respective performance metrics. Alternatively, one of the optimization objectives can be the value of a user-defined cost function of the multi-parameter design, the cost function depending from the performance metrics and/or the variables. In this case, the other objective is the uncertainty of the cost function, which is maximized. The multi-parameter designs include electrical circuit designs such as analog, mixed-signal, and custom digital circuits.

Model-building optimization

For application to analog, mixed-signal, and custom digital circuits, a system and method to improve the flow of setting up a set of simulations, a characterization, or optimization problem via an interactive circuit schematic. A system and method to visualize circuit simulation data in which at least one of the views is an enhanced, interactive schematic view.

Interactive schematic for use in analog, mixed-signal, and custom digital circuit design

A system and method of generating a set of circuit simulation data, applying data mining to for knowledge extraction from the data, and graphically presenting the extracted knowledge in a format that is easy to digest to a designer.

Data-mining-based knowledge extraction and visualization of analog/mixed-signal/custom digital circuit design flow

A system that includes a candidate generator that generates candidate vectors having as components performance specifications of an electrical circuit design. The system also includes a performance estimator that generates performance vectors of the electrical circuit design, the performance vectors having as components performance values of the electrical circuit design. The candidate vectors and the performance vectors are input into a statistical estimator that calculates a statistical parameter, for example, yield, for each candidate vector in accordance with the performance vectors. The system further includes a filter that receives the candidate vectors and their respective statistical parameters, and outputs a filtered candidate vector with its corresponding filtered statistical parameter. A display system visually represents the filtered candidate vector and its corresponding filtered statistical parameter.

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Saskatoon, Canada

Shawn Rusaw