Abstract: A model including a first co-simulation component and a second co-simulation component is analyzed. During execution of the model, the first co-simulation component outputs data to the second co-simulation component via a connection. The connection is declared as a continuous-time rate connection for input of the data into the second co-simulation component. Based on analyzing the model, the connection is identified as a discrete-continuous sample time connection based on data being communicated from the first co-simulation component to the second co-simulation component via the connection at a discrete-time rate when the model is executed in a co-simulation manner.

Abstract: Systems and methods automatically construct a realization of a model from an available set of alternative co-simulation components, where the realization meets one or more objectives, such as fidelity, execution speed, or memory usage, among others. The systems and methods may construct the realization model by setting up and solving a constrained optimization problem, which may select particular ones of the alternative co-simulation components to meet the objectives. The systems and methods may configure the realization, and execute the realized model through co-simulation. The systems and methods may employ and manage different execution engines and/or different solvers to run the realization of the model.

Abstract: An example method matches content, such as files and file snippets, using one or more scalable knowledge bases.

Abstract: A model including a first co-simulation component and a second co-simulation component is analyzed. During execution of the model, the first co-simulation component outputs data to the second co-simulation component via a connection. The connection is declared as a continuous-time rate connection for input of the data into the second co-simulation component. Based on analyzing the model, the connection is identified as a discrete-continuous sample time connection based on data being communicated from the first co-simulation component to the second co-simulation component via the connection at a discrete-time rate when the model is executed in a co-simulation manner.

Abstract: A model including a first co-simulation component and a second co-simulation component is analyzed. During execution of the model, the first co-simulation component outputs data to the second co-simulation component via a connection. The connection is declared as a continuous-time rate connection for input of the data into the second co-simulation component. Based on analyzing the model, the connection is identified as a discrete-continuous sample time connection based on data being communicated from the first co-simulation component to the second co-simulation component via the connection at a discrete-time rate when the model is executed in a co-simulation manner.

Abstract: Systems and methods automatically construct a realization of a model from an available set of alternative co-simulation components, where the realization meets one or more objectives, such as fidelity, execution speed, or memory usage, among others. The systems and methods may construct the realization model by setting up and solving a constrained optimization problem, which may select particular ones of the alternative co-simulation components to meet the objectives. The systems and methods may configure the realization, and execute the realized model through co-simulation. The systems and methods may employ and manage different execution engines and/or different solvers to run the realization of the model.

Abstract: Systems and methods automatically construct a realization of a model from an available set of alternative co-simulation components, where the realization meets one or more objectives, such as fidelity, execution speed, or memory usage, among others. The systems and methods may construct the realization model by setting up and solving a constrained optimization problem, which may select particular ones of the alternative co-simulation components to meet the objectives. The systems and methods may configure the realization, and execute the realized model through co-simulation. The systems and methods may employ and manage different execution engines and/or different solvers to run the realization of the model.

Abstract: A device may detect a user interaction, via a user interface, with a particular component of a model. The device may generate a set of components, associated with the particular component, based on detecting the user interaction with the particular component of the model. The device may cause a representation of the set of components to be provided, via the user interface, in association with the model. The representation may indicate that the set of components are associated with permitting interoperability.

Abstract: Systems and methods automatically construct a realization of a model from an available set of alternative co-simulation components, where the realization meets one or more objectives, such as fidelity, execution speed, or memory usage, among others. The systems and methods may construct the realization model by setting up and solving a constrained optimization problem, which may select particular ones of the alternative co-simulation components to meet the objectives. The systems and methods may configure the realization, and execute the realized model through co-simulation. The systems and methods may employ and manage different execution engines and/or different solvers to run the realization of the model.

Abstract: A model including a first co-simulation component and a second co-simulation component is analyzed. During execution of the model, the first co-simulation component outputs data to the second co-simulation component via a connection. The connection is declared as a continuous-time rate connection for input of the data into the second co-simulation component. Based on analyzing the model, the connection is identified as a discrete-continuous sample time connection based on data being communicated from the first co-simulation component to the second co-simulation component via the connection at a discrete-time rate when the model is executed in a co-simulation manner.

Abstract: A device may detect a user interaction, via a user interface, with a particular component of a model. The device may generate a set of components, associated with the particular component, based on detecting the user interaction with the particular component of the model. The device may cause a representation of the set of components to be provided, via the user interface, in association with the model. The representation may indicate that the set of components are associated with permitting interoperability.

Abstract: A programming element is provided that defines model attributes in response to mode change events in a graphical modeling environment. Such definition may involve any signal attribute such as dimensions, data types, complexity and sample times. Events that trigger definition of model attributes may be explicit signaling events generated by other elements, elements within the block diagram programming environment, and elements external from the environment. Implicit events may also trigger definition of model attributes, such as a change of attribute in an input signal.

Abstract: In an embodiment, a specification of a configuration subgraph is received. The configuration subgraph may graphically specify an attribute for an element in a block diagram model. A relationship may be established between the configuration subgraph and the element. The configuration subgraph may be evaluated to produce a result. The result may be used to configure the attribute of the element during or prior to a compilation of a dynamic portion of the block diagram model. The configuration subgraph may not be used during an execution of the dynamic portion of the block diagram model.

Abstract: A method and system are provided for generating code from a graphical model in a graphical modeling environment. The graphical model includes at least one signal having a data size, a data dimensionality, or both that can vary from a first time instance to a second time instance as the model executes. The size and dimensionality of the signal can vary without the use of a graphically rendered connection to convey the size and dimension information to a block associated with the signal.

Abstract: A system and method that includes line connection navigation in a block diagram by highlighting connections through navigable blocks in the diagram, edit-time label propagation along connections and through navigable blocks that can propagate labels through their ports, API to define navigability between block ports, and displaying implied connections between blocks.

Abstract: A programming element is provided that defines model attributes in response to mode change events in a graphical modeling environment. Such definition may involve any signal attribute such as dimensions, data types, complexity and sample times. Events that trigger definition of model attributes may be explicit signaling events generated by other elements, elements within the block diagram programming environment, and elements external from the environment. Implicit events may also trigger definition of model attributes, such as a change of attribute in an input signal.

Abstract: A method and apparatus to generate code to represent a graphical model formed of multiple graphical modeling components and at least one variable-sized signal is presented. Each variable-sized signal is represented using a size-vector in the generated code. The generated code is optimized by representing multiple variable-sized signals with the same size-vector such that at least two variable-sized signals share a size-vector in the generated code. The size of the variable-sized signal is capable of changing during the execution of the graphical model. The method and apparatus also identifies the owners of the variable-sized signals.

Abstract: A method and system are provided for generating code from a graphical model in a graphical modeling environment. The graphical model includes at least one signal having a data size, a data dimensionality, or both that can vary from a first time instance to a second time instance as the model executes. The size and dimensionality of the signal can vary without the use of a graphically rendered connection to convey the size and dimension information to a block associated with the signal.

Abstract: A method and system are provided for generating code from a graphical model in a graphical modeling environment. The graphical model includes at least one signal having a data size, a data dimensionality, or both that can vary from a first time instance to a second time instance as the model executes. The size and dimensionality of the signal can vary without the use of a graphically rendered connection to convey the size and dimension information to a block associated with the signal.

Abstract: Graphical programming or modeling environments, such as a block diagram environment, are disclosed in which graphical programs or models are configured using handshaking communication between entities of the graphical programs or models. The graphical programming or modeling environments provide mechanisms for the handshaking configuration of graphical programs/models before the graphical programs/models are executed in the graphical programming/modeling environments.