Solido Design Automation Inc.

Mentor Graphics Corporation

Siemens Industry Software Gmbh

Joel Cooper

Trent Lorne McConaghy

Jeffrey Dyck

Kristopher Breen

Shawn Rusaw

David Callele

Samer Sallam

Jiandong Ge

Charles Cazabon

Amit Gupta

Jason Coutu

Anthony Arkles

Patrick Drennan

Pat Drennan

Jiangdon Ge

Megan Marsh

Kyle Fisher

Sean Cocks

Trent Lome McConaghy

Ryan Silk

A computing system can implement a circuit verification tool to perform scaled sampling of parameter values in a foundry model describing parameter variations for a manufacturing process capable of fabricating an integrated circuit described in a circuit design. The computing system can simulate the circuit design with the scaled samples of the parameter values, and build a geometric model to describe a response of the circuit design to the scaled samples of the parameter values during the simulation. The geometric model can include one or more failure regions corresponding to geometric descriptions for failures of the circuit design to meet a specification during simulation with the scaled samples of the parameter values. The computing system can estimate a yield for an output of the integrated circuit described by the circuit design based on the failure regions in the geometric model.

Estimating integrated circuit yield from modeled response to scaling of distribution samples

A computer-implemented method for quickly analyzing the effect of process, voltage, temperature, and other variations when the variation analysis or circuit structure can be hierarchically composed into nested loops. The method has two main steps: first, it hierarchically generates a set of points and inserts them into a flat list of tuples, where each tuple contains a point from each level in the looping hierarchy. Second, it efficiently identifies and simulates failing tuples with the assistance of modeling to order the tuples to simulate. By using the present method, a designer does not have to simulate the full ECD at each and every statistical process point or PVT corner, which can same considerable time or compute effort.

Method and system of fast nested-loop circuit verification for process and environmental variation and hierarchical circuits

A method and system to estimate failure rates in designs. N Monte Carlo samples are drawn from the random distribution that describes process variation in the design. A subset of these samples is selected, and that subset of Nsamples are simulated (with a circuit simulator) to measure a performance value for each sample. A model is constructed, using the values of the Nprocess points as training inputs, and the corresponding Nperformance values as training outputs. The candidate Monte Carlo samples are from the N Monte Carlo samples that have not yet been simulated. Each candidate is simulated on the model to get predicted performance values, and the samples are ordered in ascending (or descending) order of the predicted performance values. Simulation of candidates samples is then begun, in that order. The sampling and simulation will stops once there is sufficient confidence that all failures are found.

Method and system for identifying rare-event failure rates

A method for finding the process, voltage, temperature, parasitics, and power settings (PVTPP) corner at which an electrical circuit design has the worst-case optimum simulated output performance. The method uses a global optimization process in a series of iterations that aim to uncover the PVTPP corner at which the ECD has the worst-case output value. By using the present method, a designer does not have to simulate the ECD at each and every PVTPP corner, which can same considerable time or compute effort. Examples using Model-Building Optimization are provided.

Method and system for verification of electrical circuit designs at process, voltage, and temperature corners

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

A method for proximity-aware circuit design where a set of layout constraint values that satisfy predetermined performance or yield goals is determined in accordance with a layout effect model. One of the layout constraint values is then selected as a constraint input to layout design, and a design layout is performed with the selected layout constraint value to provide a semiconductor circuit design for the semiconductor circuit. The set of layout constraint values can be determined by varying an instance parameter of the layout effect model to determine a set of instance parameters that satisfy the at least one predetermined performance or yield goal in accordance with the layout effect model, and determining layout constraints associated with each instance parameter of the set of instance parameters, thus providing a number of candidates in a design space that can be evaluated according to performance and/or yield tradeoffs.

Method and system for proximity-aware circuit design

For application to analog, mixed-signal, and custom digital circuits, a system and method to begin with a complex problem description that encompasses many variables from statistical manufacturing, the circuit's environment, and the circuit's design parameters, but then apply techniques to prune the scope of the problem to make it manageable for manual design and more efficient automated design, and finally use that pruned problem for more efficient and effective design.

Pruning-based variation-aware design

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

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.

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Saskatoon, Canada

Joel Cooper