2850results about "Probabilistic CAD" patented technology

A system for analyzing IC layouts and designs by calculating variations of a number of objects to be created on a semiconductor wafer as a result of different process conditions. The variations are analyzed to determine individual feature failures or to rank layout designs by their susceptibility to process variations. In one embodiment, the variations are represented by PV-bands having an inner edge that defines the smallest area in which an object will always print and an outer edge that defines the largest area in which an object will print under some process conditions.

The invention provides a method, system, and program product for determining a gradient of a parametric yield of an integrated circuit with respect to parameters of a delay of an edge of a timing graph of the circuit. A first aspect of the invention provides a method for determining a gradient of a parametric yield of an integrated circuit with respect to parameters of a delay of an edge of a timing graph of the circuit, the method comprising: conducting a statistical timing analysis; expressing a statistical circuit delay in terms of a delay of the edge; and computing a gradient of the statistical circuit delay with respect to parameters of the delay of the edge.

This invention describes computer based virtual models of complex systems, together with integrated systems and methods providing a development and execution framework for visual modeling and dynamic simulation of said models. The virtual models can be used for analysis, monitoring, or control of the operation of the complex systems modeled, as well as for information retrieval. More particularly, the virtual models in the present implementation relate to biological complex systems. In the current implementation the virtual models comprise building blocks representing physical, chemical, or biological processes, the pools of entities that participate in those processes, a hierarchy of compartments representing time-intervals or the spatial and / or functional structure of the complex system in which said entities are located and said processes take place, and the description of the composition of those entities. The building blocks encapsulate in different layers the information, data, and mathematical models that characterize and define each virtual model, and a plurality of methods is associated with their components. The models are built by linking instances of the building blocks in a predefined way, which, when integrated by the methods provided in this invention, result in multidimensional networks of pathways. A number of functions and graphical interfaces can be selected for said instances of building blocks, to extract in various forms the information contained in said models. Those functions include: a) on-the-fly creation of displays of interactive multidimensional networks of pathways, according to user selections; b) dynamic quantitative simulations of selected networks; and c) complex predefined queries based on the relative position of pools of entities in the pathways, the role that the pools play in different processes, the location in selected compartments, and / or the structural components of the entities of those pools. The system integrates inferential control with quantitative and scaled simulation methods, and provides a variety of alternatives to deal with complex dynamic systems and with incomplete and constantly evolving information and data.

A method, computer program product, and computer system for configuring a stochastic simulation scenario, wherein the stochastic simulation scenario may include one or more variables without a complete probability distribution. The stochastic simulation scenario may be executed to generate one or more results of the stochastic simulation scenario. At least a portion of the one or more variables without the probability distribution may be optimized using one or more optimization metrics on the one or more results of the stochastic simulation scenario.

An efficient method and computer program for modeling and improving stating memory performance across process variations and environmental conditions provides a mechanism for raising the performance of memory arrays beyond present levels / yields. Statistical (Monte-Carlo) analyses of subsets of circuit parameters are performed for each of several memory performance variables and then sensitivities of each performance variable to 15 each of the circuit parameters are determined. The memory cell design parameters and / or operating conditions of the memory cells are then adjusted in conformity with the sensitivities, resulting in improved memory yield and / or performance. Once a performance level is attained, the sensitivities can then be used to alter the probability distributions of the performance variables to achieve a higher yield. Multiple cell designs can be compared for performance, yield and sensitivity of performance variables to circuit parameters over particular environmental conditions in order to select the best cell design.

A computer-based system, computer-implemented method, and computer program product facilitate determining energy cost savings in an energy-consuming facility, such as a commercial building, using an artificial intelligence model, for example a neural network model, that projects or estimates the amount of energy that would have been consumed by the facility but for the implementation of energy efficiency or conservation measures. Energy savings are represented by the difference between the estimate of energy that would have been consumed but for the measures and the actual amount of energy consumed by the facility under actual conditions during a time interval after the measures have been implemented.

Correlated failure distribution for memory arrays having different groupings of memory cells is estimated by constructing memory unit models for the groupings based on multiple parameters, establishing failure conditions of the memory unit model using fast statistical analysis, calculating a fail boundary of the parameters for each memory unit model based on its corresponding failure conditions, and constructing memory array models characterized by the fail boundaries. Operation of a memory array model is repeatedly simulated with random values of the parameters assigned to the memory cells and peripheral logic elements to identify memory unit failures for each simulated operation. A mean and a variance is calculated for each memory array model, and an optimal architecture can thereafter be identified by selecting the grouping exhibiting the best mean and variance, subject to any other circuit requirements such as power or area.

A contour of a mask design for an integrated circuit is modified to compensate for systematic variations arising from non-optical effects such as stress, well proximity, rapid thermal anneal, or spacer thickness. Electrical characteristics of a simulated integrated circuit chip fabricated using the mask design are extracted and compared to design specifications, and one or more edges of the contour are adjusted to reduce the systematic variation until the electrical characteristic is within specification. The particular electrical characteristic preferably depends on which layer is to be fabricated from the mask: on-current for a polysilicon; resistance for contact; resistance and capacitance for metal; current for active; and resistance for vias. For systematic threshold voltage variation, the contour is adjusted to match a gate length which corresponds to an on-current value according to pre-calculated curves for contour current and gate length at a nominal threshold voltage of the chip.

The invention provides a method and apparatus for predicting the failure of a component using a probabilistic model of a material's microstructural-based response to fatigue. The method predicts the component failure by a computer simulation of multiple incarnations of real material behavior, or virtual prototyping. The virtual prototyping simulates the effects of characteristics that include grain size, grain orientation, micro-applied stress and micro-yield strength that are difficult to simulate with real specimens. The invention provides an apparatus for predicting the response of a component to fatigue using the method.

The present invention provides a method for designing and making a customized ophthalmic lens, such as a contact lens or an intraocular lens, capable of correcting high-order aberrations of an eye. The posterior surface of the customized contact lens is designed to accommodate the corneal topography of an eye. The design of the customized ophthalmic lens is evaluated and optimized in an optimizing routine using a computational model eye that reproduces the aberrations and corneal topography of an eye. The present invention also provides a system and method for characterizing the optical metrology of a customized ophthalmic lens that is designed to correct aberrations of an eye. Furthermore, the present invention provides a business model and method for placing an order for a pair of customized ophthalmic lenses.

The invention involves generating and presenting, typically electronically, a number of design alternatives to persons who are participating in the design, selection, or market research exercise. The participants (referred to as “selectors”) transmit data indicative of their preferences among or between the presented design alternatives, and that data is used to derive a new generation of design alternatives or proposals. The new designs are generated through the use of a computer program exploiting a genetic or evolutionary computational technique. The process is repeated, typically for many iterations or cycles.

Models are generated using a variety of tools and features of a model generation platform. For example, in connection with a project in which a user generates a predictive model based on historical data about a system being modeled, the user is provided through a graphical user interface a structured sequence of model generation activities to be followed, the sequence including dimension reduction, model generation, model process validation, and model re-generation.In connection with a project in which a user generates a predictive model based on historical data about a system being modeled, and in which the project includes a series of user choice points and actions or parameter settings that govern the generation of the model based on rules, which direct the user to select and apply an optimal model.

A statistical technique is used to estimate the status of switching devices (such as circuit breakers, isolator switches and fuses) in distribution networks, using scares (i.e., limited or non-redundant) measurements. Using expected values of power consumption, and their variance, the confidence level of identifying the correct topology, or the current status of switching devices, is calculated using any given configuration of real time measurements. Different topologies are then compared in order to select the most likely topology at the prevailing time. The measurements are assumed as normally distributed random variables, and the maximum likelihood principle or a support vector machine is applied.

A system and a method are provided for performing an integrated uncertainty analysis on a system having interacting modules. The interaction of the modules includes data transfer between the modules with the output of one module being indicative of the input of another module. An uncertainty analysis is performed on each module based on given probability density functions of each input to the module. The uncertainty analysis may include developing a deterministically equivalent model for one or more modules. Data may be provided from one module to another in a uniform format. Thus, two or more modules may be integrated with uncertainties in the inputs of one module being effectively propagated to the inputs of another module. A plurality of modules may thus be modeled as a single integrated system. The integrated system may be replaced with a deterministically equivalent model, preferably of a further reduced order. In this manner, key uncertainties in particular inputs may be isolated. Once these inputs are identified, resources may be effectively allocated to minimize the impact of those inputs on the variability of the results.

Embodiments of the present invention provide methods for optimizing a lithographic projection apparatus including optimizing projection optics therein, and preferably including optimizing a source, a mask, and the projection optics. The projection optics is sometimes broadly referred to as “lens”, and therefore the joint optimization process may be termed source mask lens optimization (SMLO). SMLO is desirable over existing source mask optimization process (SMO), partially because including the projection optics in the optimization can lead to a larger process window by introducing a plurality of adjustable characteristics of the projection optics. The projection optics can be used to shape wavefront in the lithographic projection apparatus, enabling aberration control of the overall imaging process. According to the embodiments herein, the optimization can be accelerated by iteratively using linear fitting algorithm or using Taylor series expansion using partial derivatives of transmission cross coefficients (TCCs).

A method, system, and computer readable medium for facilitating a process performed by a semiconductor processing tool. The method includes inputting data relating to a process performed by the semiconductor processing tool, and inputting a first principles physical model relating to the semiconductor processing tool. First principles simulation is performed using the input data and the physical model to provide a virtual sensor measurement relating to the process performed by the semiconductor processing tool, and the virtual sensor measurement is used to facilitate the process performed by the semiconductor processing tool.

The present invention relates to water events modeling including flood, the number one natural disaster in the world. Specifically, the present invention generates models of water events consist of one or multiple outputs from various modeling processes. It also generates analytics of water events, and integrating the water models for machine and human-eyes consumption. Further, the present invention produces derivatives, tools, and informational services for various purposes, such as, flood risk assessment; flood determination; and insurance rating. The present invention is the process and systems of producing one or multiple models of water events and derivatives, based on various inputs. For modeling water events at a given location and in a timely fashion, the present invention prepares, aggregates, integrates, and maintains all relevant inputs in one system. The input data include various information, such as, water events' extent, flooded areas, flood plain, inundated areas, and measurement of water condition. The input datasets also include various other data, such as, terrain elevation data, land use land cover data, soil conductivity, water gauge measurements, and hydrologic regression equations for calculating flows. The inputs further include hydrologic modeling algorithms, hydraulic modeling algorithms, geospatial algorithms, and local or remote data of real-time water conditions acquired through machine services.

This invention describes computer based systems and methods for modeling and simulation of biochemical networks of pathways, including metabolic, signal transduction and regulatory pathways within a cell or across cells. The invention comprises systems and methods for building the models and for using the models for analysis and information retrieval, for determining the effect that modulating one or more reactions in a biochemical pathway has on an operation of the biochemical pathway, and for simulating or predicting an altered physiological state of cells.

A method for specifying a multi-component composition without human intervention includes customer specification of at least two physical property limitations, and determination of a recommended composition meeting those limitations using a continuous model relating the physical properties to the compositional variables. The method may extend to supplying a multi-component composition by further including one or more of calculating the cost of the recommended composition, calculating the price of the recommended composition, formulating a contracted amount of the recommended composition, and billing for a contracted amount of the recommended composition.

A method for Fault Tree Map generation employs to transformation of Fault Trees of production installation, specific installation, technical system (Hardware and integrated Hardware / Software) to new Fault Tree diagram (Fault Tree Map), which permits drastically compact the Fault Tree depiction and facilitates performing of the Fault Tree qualitative analysis, including evaluation of combination of latent failures and evident failures, repeated events and critical events position influence, and failure propagation potentiality, besides facility of localization of each Fault Tree logical Gate and relevant failures in the fault tree printed report. Generation takes place using special symbols, which permit to reflect the Fault Tree logic, present all Fault Tree failures with graphically identification of the failure type, and show the failure repetition and also the failure critically (importance) to Fault Tree Top Event probability. The method presents exceptional advantages to analysis of large-scale, extended Fault Trees, allowing vastly decrease the time of analysis and elevate the analysis quality and Fault Tree perception, including for specialists, who are not the Fault Tree authors.

Statistical timing analysis methods for circuits are described which compensate for circuit elements having correlated timing delays with a high degree of computational efficiency. An quadratic timing model is used to represent each delay element along a circuit path, wherein each element's delay has a first-order relationship to local variations and a second-order relationship to global variations. Propagation of the modeled delays through the circuit is efficiently done via straightforward ADD operations where an input propagates through another element in a circuit path, and via a MAX operation (or an approximation thereof) where two or more inputs merge at an intersection. The inputs to the MAX operator can be tested for gaussianity, and can be processed by the MAX operation (or its approximation) if they are substantially gaussian. Otherwise, they may be stored in a tuple for processing at later points along the circuit path.

A method, system and computer readable medium for controlling a process performed by a semiconductor processing tool includes inputting data relating to a process performed by the semiconductor processing tool, and inputting a first principles physical model relating to the semiconductor processing tool. First principles simulation is then performed using the input data and the physical model to provide a first principles simulation result, and the first principles simulation result is used to control the process performed by the semiconductor processing tool.

A machine learning module may generate a probability distribution from training data including labeled modeling data correlated with reflection data. Modeling data may include data from a LIDAR system, camera, and / or a GPS for a target environment / object. Reflection data may be collected from the same environment / object by a radar and / or an ultrasonic system. The probability distribution may assign reflection coefficients for radar and / or ultrasonic systems conditioned on values for modeling data. A mapping module may create a reflection model to overlay a virtual environment assembled from a second set of modeling data by applying the second set to the probability distribution to assign reflection values to surfaces within the virtual environment. Additionally, a test bench may evaluate an algorithm, for processing reflection data to generate control signals to an autonomous vehicle, with simulated reflection data from a virtual sensor engaging reflection values assigned within the virtual environment.

An apparatus and method are provided for performing verification tests for a design of a data processing system. The apparatus comprises a system under verification representing at least part of the design of the data processing system, and a transactor for connecting to an interface of the system under verification, and for generating signals for input to the system under verification via the interface during performance of the verification tests. Profile storage stores a profile providing a statistical representation of desired traffic flow at the interface, the statistical representation providing statistical information for a plurality of traffic attributes and also identifying at least one dependency between such traffic attributes. The transactor then references the profile in order to determine the signals to be generated, such that the signals generated take account of the specified dependencies identified in the profile. Such a mechanism enables the transactor to more realistically replicate the traffic flow that will be observed in the real system. Another aspect to the present invention provides a mechanism for generating such profiles.

According to the multi-aircraft cooperative air combat planning method and system based on deep reinforcement learning provided by the invention, a combat aircraft is regarded as an intelligent agent, a reinforcement learning agent model is constructed, and a network model is trained through a centralized training-distributed execution architecture, so that the defect that the exploratory performance of a network model is not strong due to low action distinction degree among different entities during multi-aircraft cooperation is overcome; and by embedding expert experience in the reward value, the problem that a large amount of expert experience support is needed in the prior art is solved. Through an experience sharing mechanism, all agents share one set of network parameters and experience playback library, and the problem that the strategy of a single intelligent agent is not only dependent on the feedback of the own strategy and the environment, but also influenced by the behaviors and cooperation relationships of other agents is solved. By increasing the sampling probability of the samples with large absolute values of the advantage values, the samples with extremely large or extremely small reward values can influence the training of the neural network, and the convergence speed of the algorithm is accelerated. The exploration capability of the intelligent agent is improved by adding the strategy entropy.