Cadence Design Systems, Inc.

Hongzhou Liu

Wangyang Zhang

Hui Joyce Zhang

Hui Xu

Rodney Phelps

Michael Tian

Elias Lee Fallon

Richard John O'Donovan

Saurabh Kumar Tiwary

Hua Luo

David Allan White

Yu Liu

Amith Singhee

Regis R Colwell

Rob A Rutenbar

Prakash Gopalakrishnan

An-Chang Deng

Sandipan Ghosh

Joshua Alexander Baudhuin

Jushan Xie

Vuk Borich

Preeti Kapoor

Sravasti Gupta Nair

Shang Li

Juno Lin

Iain Farquharson

Ron Pyke

Catherine Bunting

Lorenz Neureuter

Chris (Shyh-Chang) Lin

Rahaprian Premavathi Mudiarasan

Ankur Duggal

Jiulong Zhang

Allen You

Daniel Da Fonseca Munford Argollo

Jianzhou Zhao

Thomas Richards

Daniel De Fonseca Munford Argollo

Stephan Weber

Shikha Sharma

Glen Clark

The present disclosure relates to a computer-implemented method for genetic placement of analog and mix-signal circuit components. Embodiments may include receiving an unplaced layout associated with an electronic circuit design and grouping requirements. Embodiments may also include identifying one or more instances that need to be placed in the unplaced layout and areas of the unplaced layout configured to receive the instances. Embodiments may further include analyzing one or more instances that need to be placed in the unplaced layout and the areas of the unplaced layout configured to receive the instances, wherein analyzing is based upon a row-based data structure. Embodiments may also include determining a location and an orientation for each of the one or more instances based upon the genetic algorithm and generating a placed layout based upon the determined location and orientation for each of the instances.

System, method, and computer program product for analog and mix-signal circuit placement

Embodiments include herein are directed towards a method for electronic circuit design. Embodiments may include receiving, using a processor, an electronic design library including a plurality of design rules. Embodiments may include generating a routing graph, based upon, at least in part, the plurality of design rules, wherein the routing graph is a virtual representation of all of the available routing space for all routing layers associated with an electronic design. Embodiments may further include dynamically updating the routing graph at a graphical user interface, based upon, at least in part, a creation of a routing segment or a via at the graphical user interface.

System and method for routing in an electronic design

A system, method, and computer program product for predicting mismatch contribution in an electronic environment. Embodiments may include modeling, using a processor, a discrete output mismatch contribution problem using sparse logistic regression to generate a mismatch contribution model and applying a cross-validation approach to increase a complexity of the mismatch contribution model. Embodiments may further include computing one or more mismatch contribution values from the mismatch contribution model and defining at least one sizing constraint or determining a worst case result associated with a sampling process based upon, at least in part, the one or more mismatch contribution values.

System and method for device mismatch contribution computation for non-continuous circuit outputs

Disclosed is an improved approach to implement analog or mixed-signal designs. A method, system, and computer program product are provided to fully automate the analog placement step using a virtual grouping methodology which considers variable components and uses a genetic placement algorithm to find the best placement solution which fully respects the analog constraints defined by a user or auto identified by a tool.

Automatic placement of analog design components with virtual grouping

A method for performing multiple simulations for a circuit using a first plurality of samples is provided. The method includes obtaining a model of the circuit based on a result of the simulations, determining a failure rate and a confidence interval of the failure rate for the circuit with the performance model. The method includes determining an importance distribution based on the failure rate for the first plurality of samples, wherein the importance distribution is indicative of a probability that a sample value for the circuit will fail the simulation, selecting a second plurality of samples based on the importance distribution, performing a second set of simulations using the second plurality of samples to reduce the confidence interval of the failure rate. When the confidence interval is larger than a value, obtaining an updated performance model and performing new Monte Carlo simulations with new samples.

Sampling selection for enhanced high yield estimation in circuit designs

A method for determining the tail performance of an integrated circuit is described. The method includes simulating the integrated circuit over samples to obtain values for circuit specifications and sorting the circuit specifications based on an expected number of samples. The method also includes arranging a sequence of samples from the universe according to a sequence in the group of circuit specifications, simulating the integrated circuit with one of the sequence of samples to obtain at least one circuit specification, removing the at least one circuit specification from the group when it satisfies the stop criterion, and modifying a model for a second circuit specification based on the at least one circuit specification. The computer-implemented method also includes reordering the group of circuit specifications based on the model and determining an integrated circuit performance based on a simulation result for the at least one circuit specification.

Parallel Monte Carlo sampling for predicting tail performance of integrated circuits

A method for visualizing a performance distribution of an integrated circuit (IC) design is provided. The method includes determining a yield limit based on a group of Monte Carlo simulations of the IC design, and a functional yield, and selecting an initial yield based on an initial specification value from the group of Monte Carlo simulations. The method also includes selecting additional yield values based on additional specification values and on the group of Monte Carlo simulations of the IC design, wherein the low yield values are estimated using Kernel Density Estimation, and the high yield values are estimated using repeated binary search. The cumulative distribution function and probability density function for a performance of the IC design are estimated based on the additional yield values and the additional specification values. Also, the method includes obtaining a quantile representation for the performance of the IC design from the cumulative distribution function.

Estimation and visualization of a full probability distribution for circuit performance obtained with Monte Carlo simulations over scaled sigma sampling

A system, methods, and a computer program product for estimating a yield and creating corners of a circuit design with the aid of a failure boundary classification. The system, methods and computer program product provide for determining, based on how many sampling factors have failures, whether data samples are sufficient as input to scaled-sigma sampling. If the data samples are insufficient, the failure boundary classification is usable to determine whether the yield is high enough to meet a yield target. A design corner can be located by applying a binary search to results of scaled-sigma sampling. The failure boundary classification can aid in setting up the search.

Failure boundary classification and corner creation for scaled-sigma sampling

Methods and systems are provided. In one aspect, a method for parallel extraction of worst case corners of a number of electronic design automation (EDA) simulations includes generating multiple initial EDA simulation results for a number of specifications of an integrated circuit based on a first algorithm. For each specification, a respective first set of input samples is generated based on a second algorithm using generated multiple initial simulation results. Using a third algorithm, two or more of the respective first set of input samples are merged based on a criterion to generate a respective second set of input samples. For each specification, a first set of simulation results is generated using the respective second set of input samples. The worst case corners for the specifications are determined by applying in parallel local optimization to the first set of simulation results.

Parallel extraction of worst case corners

Method for estimating a yield of a post-layout circuit design is provided. In one aspect, a method includes obtaining a first pre-layout parameter and a second pre-layout parameter from pre-layout simulation samples of a circuit. The method also modeling a prior distribution of a first post-layout parameter and a second post-layout parameter based on the first pre-layout parameter, the second pre-layout parameter, a first hyper-parameter, and second hyper-parameter. The method further includes calculating the first hyper-parameter and the second hyper-parameter using a cross-validation, obtaining the first post-layout parameter and the second post-layout parameter based on the first hyper-parameter and the second hyper-parameter and estimating the yield of the circuit design using a non-normal distribution parameterized by the obtained first post-layout parameter and second post-layout parameter.

Yield estimation for a post-layout circuit design

A method for determining mismatch variation of circuit components in a circuit is provided. The method includes determining a mismatch contribution for a specification of an integrated circuit design and displaying a list of components in the circuit design sorted according to the mismatch contribution. The method also includes displaying an adjustable scale for a size of the component, modifying the circuit design according to with the size of the component adjusted according to a user input to the adjustable scale, determining an adjusted mismatch contribution of the component, and displaying in the list of components a modified value of the mismatch contribution, and a modified value of an overall standard deviation for the specification in the circuit design.

Interactive platform to predict mismatch variation and contribution when adjusting component parameters

An improved approach is provided to provide fast access to waveform visualizations for electronic designs. Data reduction is performed on the waveform data, where the quantity of the waveform data is reduced in an intelligent manner, such that the reduced waveform data still retains sufficient data fidelity for accurate data analysis and waveform visualization. The reduced data can then be displayed in an accelerated manner. From the display of the reduced data, this allows the user to select only the specific one or more waveforms for which the user seeks viewing of the full waveform data.

Method and system to accelerate visualization of waveform data

A method including separating multiple signal waveforms into multiple blocks forming a sequence is provided. Each of the blocks includes at least a portion of each of the multiple signal waveforms. The method includes identifying a shared time portion and a shared signal portion for the signal waveforms within a first block from the multiple blocks and selecting a format for the first block based on a block size of the first block and a block read time of the first block. The method also includes compressing data in the first block based on the shared time portion, the shared signal portion, a preceding block and a subsequent block in the sequence, and storing the first block in a memory based on the format selected for the first block.

Adaptive lossless compression in analog mixed signal environments

A system, method, and computer program product for reducing the number of Monte Carlo simulation samples required to determine if a design meets design specifications. The worst sample for each specification acts as a design corner to substitute for a full design verification. Embodiments determine the maximum number of samples needed, perform an initial performance modeling using an initial set of samples, and estimate the failure probability of each of the remaining samples based on the performance model. Embodiments then simulate remaining samples with a computer-operated Monte Carlo circuit simulation tool in decreasing design specification model accuracy order, wherein the sample predicted most likely to fail each specification is simulated first. Re-use of simulation results progressively improves models. Probability based stop criteria end the simulation early when the worst samples have been confidently found. A potential ten-fold reduction in overall specification verification time may result.

Efficient extraction of the worst sample in Monte Carlo simulation

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Sewickley, PA, United States of America

Hongzhou Liu