Synopsys, Inc.

Yong-Seog Oh

Victor Moroz

Stephen Lee Smith

Michael C Shaughnessy-Culver

Jie Liu

Pratheep Balasingam

Terry Sylvan Kam-Chiu Ma

Kyuho Lee

Ashutosh Kumar

Roughly described, a task control system for managing multi-scale simulations receives a case/task list which identifies cases to be evaluated, at least one task for each of the cases, and dependencies among the tasks. A module allocates available processor cores to at least some of the tasks, constrained by the dependencies, and initiates execution of the tasks on allocated cores. A module, in response to completion of a particular one of the tasks, determines whether or not the result of the task warrants stopping or pruning tasks, and if so, then terminates or prunes one or more of the uncompleted tasks in the case/task list. A module also re-allocates available processor cores to pending not-yet-executing tasks in accordance with time required to complete the tasks and constrained by the dependencies, and initiates execution of the tasks on allocated cores.

Adaptive parallelization for multi-scale simulation

An electronic design automation tool includes an application program interface API which includes a set of parameters and procedures supporting atomistic scale modeling of electronic materials. The procedures include a procedure to execute first principles calculations, a procedure to process results from the first principles calculations to extract device scale parameters from the results, a procedure to determine whether the extracted device scale parameters lie within a specified range. The procedures also include a procedure to parameterize an input parameter of a first principles procedure, including a procedure to execute a set of DFT computations across an input parameter space to characterize sensitivity of one of the intermediate parameter and the output parameter. Also included is a procedure to execute a second set of DFT computations across a refined input parameter space. The procedures include a procedure that utilizes DFT computations to parameterize the force field computations.

First principles design automation tool

Electronic design automation modules for simulate the behavior of structures and materials at multiple simulation scales with different simulation modules.

Simulation scaling with DFT and non-DFT

A system for evaluating candidate materials for fabrication of integrated circuits includes a data processor coupled to a memory. Roughly described, the data processor is configured to: calculate and write to a first database, for each of a plurality of candidate materials, values for each property in a set of intermediate properties; calculate and write to a second database, values for a selected target property for various combinations of values for the intermediate properties and values describing candidate environments; and for a particular candidate material and a particular environment in combination, determine values for the intermediate properties for the candidate material by reference to the first database, and determine the value of the target property for the candidate material by querying the second database with, in combination, (1) the determined intermediate property values of the candidate material and (2) a value or values describing the particular environment.

Mapping intermediate material properties to target properties to screen materials

Computer system provided with a control module for controlling ab initio atomic structure modules for simulating the behavior of structures and materials at multiple scales with different modules, for purposes of evaluating such structures and materials for use in integrated circuit devices. The computer system can simulate the behavior of structures and materials at atomic scale with parameters or a configuration that varies across iterative transformations.

Atomic structure optimization

Roughly described, a system for estimating an effective channel length of a 3D transistor having a gate length below 20 nm involves estimating an effective volume of the channel and a cross-sectional area of the channel, and estimating the effective channel length as the ratio of effective volume to cross-sectional area. Preferably the effective volume is estimated as the sum of the Voronoi volumes within containing boundaries of the channel, excluding those volumes having a dopant concentration above the source/drain dopant concentration at the carrier injection point. The containing boundaries can be identified using geometry data describing the transistor, particularly the data identifying inner surfaces of the gate dielectric. The estimated effective channel length can be used in TCAD level analysis of the transistor and calculating characteristics of the transistor as needed for circuit simulation.

Estimation of effective channel length for FinFETs and nano-wires

Electronic design automation modules include a first tool and a second tool. The first tool includes ab initio simulation procedures configured to use input parameters to produce information about a band structure of a simulated material on a first simulation scale specified at least in part by the input parameters. The second tool includes a simulation procedure configured to used information about the band structure of the simulated material produced by the first tool to extract parameters on a second simulation scale larger than the first simulation scale.

Multi-scale simulation including first principles band structure extraction

Roughly described, a method is provided to approximate chemical potentials of elements in ternary and quaternary compound semiconductors, for example III-V semiconductors. In embodiments of the present invention, three, four, or more relationships are solved together to find approximated chemical potentials for each group III element and each group V element. The first relationship relates total energy of a defect-free system to the sum, over all of the group III and group V elements, of (a) provisional chemical potential for the respective element, times (b) number of atoms of the respective element within a supercell. The second relationship describes a stoichiometric balance relationship between total atomic density of all group III atoms and total atomic density of all group V atoms. The other relationship or relationships balance mole fraction ratio between group III atoms, or between group V atoms.

Method to approximate chemical potential in a ternary or quaternary semiconductor

Roughly described, a technique for approximating a target property of a target material is provided. For each material in a plurality of anchor materials, a correspondence is provided between the value for a predetermined index property of the material and a value for the target property of the material, the values of all the index properties being different. A predictor function is identified in dependence upon the correspondence. A computer system determines a value for the target property for the target material in dependence upon the predictor function and a value for the index property for the target material. The determined value for the target property for the target material is reported to a user. The correspondence can be provided in a database on a non-transitory computer readable medium. The correspondence can be determined experimentally or analytically for each material in a plurality of anchor materials.

Characterizing target material properties based on properties of similar materials

An electronic design automation tool includes an application program interface API. The API includes a set of parameters and procedures supporting atomistic scale modeling of electronic materials. The procedures include a procedure to execute first principles calculations, a procedure to process results from the first principles calculations to extract device scale parameters from the results, and a procedure to determine whether the device scale parameters extracted from the results lie within a specified range of the stored information for the material. The procedures also include a procedure to parameterize an input parameter of a first principles procedure, including a procedure to execute a set of DFT computations across an input parameter space to characterize sensitivity of one of the intermediate parameter and the output parameter. Also included is a procedure to execute a second set of DFT computations across a refined input parameter space. Additional procedures include a first atomistic scale procedure to produce a set of preliminary configurations for the specified material, and a second atomistic scale procedure that utilizes DFT computations to refine the preliminary configurations and to produce the parameter set using refined configurations. The procedures include a procedure that utilizes DFT computations to parameterize the force field computations.

Electronic design automation modules simulate the behavior of structures and materials at atomic scale with parameters or a configuration that varies across iterative transformations.

Electronic design automation to simulate the behavior of structures and materials at multiple simulation scales with different simulators.

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Pleasanton, CA, United States of America

Yong-Seog Oh