Abstract: A system and method may generate executable models having message sending objects and message receiving objects. A message may include a fixed data payload, and the message may persist for only a determined time interval of a total execution or simulation time of model. Message queues may be established for the messages, and the queues may have attributes. The model may include a state-based portion having states and transitions. States may be configured to generate and send messages, and to receive and process messages. In addition, transitions may be guarded by particular messages. The system and method also may generate standalone code, such as source code, for the model. The standalone code may include code that establishes a message passing service to support the sending and receiving of messages.

Abstract: In an embodiment, a system may receive information regarding a group of physical devices; receive information regarding a set of functional blocks associated with a functional model; and receive mapping information that indicates a mapping between the set of functional blocks and one or more physical devices of the group of physical devices. The system may further generate at least one functional effect associated with the functional model. The generating may be based on: the set of functional blocks, the mapping information, and the information regarding the one or more physical devices. The system may also store or output the at least one functional effect.

Abstract: A system may receive a model, extract information from the model, form a group of tags using the extracted information, and associate the group of tags with the model. The system may further receive a search query including one or more sequences of characters and determine whether to provide the model in a list of models created for the search query, based on the one or more sequences of characters and the group of tags.

Abstract: A device receives information associated with a functional model, and generates the functional model based on the received information and with a technical computing environment (TCE), where the functional model including nodes, inputs, and outputs. The device also automatically detects architecture information from an architecture model associated with the functional model, and automatically assigns, based on the architecture information, at least one signal between two nodes of the functional model, a node and an input of the functional model, or a node and an output of the functional model. The device obtains information for code generation based on the assigned at least one signal, and stores the information for code generation.

Abstract: A system and method may generate executable models having message sending objects and message receiving objects. A message may include a fixed data payload, and the message may persist for only a determined time interval of a total execution or simulation time of model. Message queues may be established for the messages, and the queues may have attributes. The model may include a state-based portion having states and transitions. States may be configured to generate and send messages, and to receive and process messages. In addition, transitions may be guarded by particular messages. The system and method also may generate standalone code, such as source code, for the model. The standalone code may include code that establishes a message passing service to support the sending and receiving of messages.

Abstract: Exemplary embodiments allow executable graphical models, such as block diagram models, to be graphically partitioned for execution on concurrent computing resources. Embodiments allow model components to be grouped into subtasks that are affiliated with tasks associated with concurrent computing resources. Tasks and sub graphs can be mapped to concurrent computing resources according to characteristics, such as sample time, solver type, etc. Embodiments further allow mappings to be visually indicated to a user via various display techniques including color, text, icons, shading, grouping of identifiers, etc. Concurrently executing portions of a model allows model results to be obtained faster than can be obtained when models are executed on a single computing resource, such as a single processor.

Abstract: A system and method may generate executable block diagrams in which at least some of the blocks run in accordance with message-based execution semantics. A message may include an input data payload that does not change over time, and the message may persist for only a determined time interval during execution of block diagram. A message-based execution engine may control execution of message-based blocks in which a source block may generate a message at a particular point in time, the message may be sent to one or more destination blocks triggering execution of those blocks, and the message may be destroyed on or after a determined time interval. Other execution domains, such as a time-based or state-based execution domain, may be provided, and the system may implement a hybrid execution model. A verification engine may provide one or more tools for evaluating and verifying operation of message-based blocks.

Abstract: A system may receive a model, extract information from the model, form a group of tags using the extracted information, and associate the group of tags with the model. The system may further receive a search query including one or more sequences of characters and determine whether to provide the model in a list of models created for the search query, based on the one or more sequences of characters and the group of tags.

Abstract: A system and method may generate executable block diagrams in which at least some of the blocks run in accordance with message-based execution semantics. A message may include an input data payload that does not change over time, and the message may persist for only a determined time interval during execution of block diagram. A message-based execution engine may control execution of message-based blocks in which a source block may generate a message at a particular point in time, the message may be sent to one or more destination blocks triggering execution of those blocks, and the message may be destroyed on or after a determined time interval. Other execution domains, such as a time-based or state-based execution domain, may be provided, and the system may implement a hybrid execution model. A verification engine may provide one or more tools for evaluating and verifying operation of message-based blocks.

Abstract: Exemplary embodiments allow executable graphical models, such as block diagram models, to be graphically partitioned for execution on concurrent computing resources. Embodiments allow model components to be grouped into subtasks that are affiliated with tasks associated with concurrent computing resources. Tasks and sub graphs can be mapped to concurrent computing resources according to characteristics, such as sample time, solver type, etc. Embodiments further allow mappings to be visually indicated to a user via various display techniques including color, text, icons, shading, grouping of identifiers, etc. Concurrently executing portions of a model allows model results to be obtained faster than can be obtained when models are executed on a single computing resource, such as a single processor.