The Mathworks, Inc.

Biao Yu

Peter S Szpak

James E Carrick

Matthew J Englehart

Yuan Cao

Alongkrit Chutinan

Ebrahim Mehran Mestchian

Murali K Yeddanapudi

Arwen M Warlock

Pieter Johannes Mosterman

Jim Carrick

Systems and methods may generate code, for a model, with one or more service access points generated and at locations in the code based on an analysis of model constraints and deployment specifications (e.g., RTE specifications or OS specifications). The systems and methods may analyze the model and identify a functionality that needs an RTE service. The system and methods may receive deployment specifications. The systems and methods may generate code for the model, where an analysis of model constraints and the deployment specifications determine which service access points are generated and where in the code the service access points are located. In an embodiment, the code may be executed by different RTEs. In an embodiment, the systems and methods may determine, based on the analysis of the model constraints and the deployment specification, one or more admissible implementations for an RTE service that may be implemented in different ways.

Systems and methods for generating service access points for RTE services in code or other RTE service information for use with the code

Systems and methods may aggregate and organize implicit and explicit initialization, reset, and termination operations defined throughout the hierarchy of an executable. The systems and methods may analyze the model and identify implicit and explicit initialization, reset, and termination operations defined at various hierarchical levels. The systems and methods may aggregate the implicit and explicit initialization, reset, and termination operations into an initialize callable unit, a reset callable unit, and a termination callable unit. The systems and methods may apply optimizations to the callable units, and resolve conflicts. The systems and methods may define a single entry point for each of the initialize, reset, and termination callable units.

Systems and methods for aggregating implicit and explicit event code of executable models

Systems and methods decouple model components from a model execution style for which the model components are created, and the model components may be utilized in parent models having different execution styles. A model component may be partitioned into executable entities, and the entry points of the executable entities and their call styles may be identified. An adaptation layer that includes access points for the entry points may be constructed. The model component, including the adaptation layer, may be included in the model, and connection elements of the parent model may be connected to the access points of the adaptation layer. The execution call styles associated with the connection elements of the parent model may be bound to the execution call styles of the entry points as originally designed. The adaptation layer may manage translation of call styles and may coordinate scheduling of data communication with the model component.

Systems and methods for extracting adjustable attributes of model components

A device may receive a model including a group of blocks, and may receive a command to execute the model. The device may assign a parameter sample time to a subset of blocks of the group of blocks. The parameter sample time may permit a block, of the subset of blocks, to be executed based on a parameter change event detected during the execution of the model. The device may cause the model to be executed after assigning the parameter sample time to the subset of blocks. The device may detect a parameter change event, associated with the model, prior to the execution of the model being completed. The parameter change event may include an event that is external to the execution of the model. The device may cause at least one block, of the subset of blocks, to be executed based on the detecting the parameter change event.

Scheduling and executing model components in response to un-modeled events detected during an execution of the model

A system for providing model level protection for resources holding data accessed by multiple tasks in a model is discussed. The protection occurs at the model level so that the protection mechanism does not interfere with model dynamics. Resources concurrently accessed by multiple tasks are identified so that a unified protection mechanism can be applied to the resource. A user interface may be provided which enables the selection of a particular type of protection mechanism for the data in the resource. User supplied protection mechanisms may also be implemented.

Data transfer protection in a multi-tasking modeling environment

Embodiments can include computer-implemented methods or non-transitory computer readable media storing executable instructions. The method or instructions can perform execution scheduling for code generated from an executable graphical model, where the generated code is executed on a target. The method/instructions can perform execution scheduling for a first code portion having a first execution rate, and a second code portion having a second execution rate that is temporally related to the first execution rate. The execution scheduling can account for target environment characteristics obtained from a target, can use an execution schedule, and can account for optimizations related to the first code portion or the second code portion. The method/instructions can further schedule execution of the first code portion and the second code portion in generated executable code based on the performing.

Scheduling generated code based on target characteristics

An embodiment can include one or more computer readable media storing executable instructions for performing execution scheduling for code generated from an executable graphical model. The media can store instructions for accessing a first code portion having a first priority, and a second code portion having a second priority, where the second priority has a relationship with the first priority. The media can store instructions for accessing target environment characteristics that indicate a performance of the target environment, and for performing execution scheduling for the first code portion and the second code portion, the execution scheduling taking into account the target environment characteristics, the execution scheduling using an execution schedule. The media can also store instructions for scheduling execution of the first code portion and the second code portion in the generated executable code based on the execution schedule, the generated executable code adapted for execution in the target environment.

When executing a graphical model of a dynamic system that includes two or more concurrently executing sets of operations, a processor is configured to create a first buffer and a second buffer within the executable graphical model. A first set of operations is configured to write data to the first buffer during a first execution instance of the first set of operations. The first set of operations is configured to write data to the second buffer during a second execution instance of the first thread. A second set of operations is configured to read the data from the first buffer during an instance of the second thread that executes contemporaneously with the second execution instance of the first set of operations. Determinations regarding access to the first buffer and second buffer by the first thread and second thread are self-contained within the first thread and second thread, respectively.

Data sharing in high-fidelity simulation and real-time multi-core execution

Implementing user-selectable concurrent access protection mechanism in a multi-tasking modeling environment

Data transfer protection in a multi-tasking modeling environment having a protection mechanism selected by user via user interface

Programming or modeling environments in which programs or models are simulated or executed with tunable sample times are disclosed. The tunable sample times can be changed during the simulation or execution of the programs or models without recompiling the programs or models. The sample times are parameterized and the value of the sample times is changed during the simulation or execution of the programs or models. The sample times may be changed manually by a user. Alternatively, the sample times may be automatically changed by programmatically defining when and how the sample times are determined.

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Sharon, MA, United States of America

Biao Yu