Multicore programming, or modeling for concurrent execution, helps you to create concurrent systems for deployment on multicore processor and multiprocessor systems. Examples of such systems are signal-processing and plant-control systems. Simulink® partitioning and mapping techniques help you to overcome common challenges in designing systems for concurrent execution.
The figure shows a sample system with multiple functions designed to execute on a CPU- and FPGA-based multiprocessor system. The system is partitioned into multiple components that are mapped to the CPU task scheduler or the FPGA.
To learn the fundamentals of multicore programming, see Concepts in Multicore Programming. For information on how to design systems for concurrent execution in Simulink, see Multicore Programming with Simulink.
|Create or convert configuration for concurrent execution|
|Add tasks or triggers to selected architecture of model|
|Delete triggers and tasks from selected architecture of model|
|Find objects under architecture object|
|Get configuration parameters of architecture objects|
|Import and select target architecture for concurrent execution environment for model|
|Generate profile report for model configured for concurrent execution|
|Add custom target architecture to concurrent execution target architecture selector|
|Set architecture object properties|
|Configure concurrent execution data transfers|
Learn how to configure your Simulink model to take advantage of concurrent execution.
Choose or define a target architecture for a model configured for concurrent execution.
Add tasks, create partitions, and map individual tasks to partitions using explicit partitioning.
Specify options for handling data transfers between concurrently executing partitions.
Configure a model for concurrent execution using explicit partitioning and deploy it to a target.
This example shows how to implement data parallelism for a system in a Simulink model.
Learn how to implement task parallelism for a system in a Simulink model.
This example shows how to implement pipelining for a system in a Simulink model.
This example shows how to take advantage of executing code on a multicore processor by graphical partitioning.
This example shows you how to take advantage of a multicore processor target with FPGA acceleration by graphically partitioning a model.
This example illustrates how to take advantage of executing multithreaded code on a multicore processor using graphical partitioning.
Theory relevant to modeling for concurrent execution.
Modeling for concurrent execution using Simulink.
Learn about the key differences between implicit and explicit partitioning.
Parameters for configuring tasks for concurrent execution
This tab displays the data transfer options for configuring models for targets with multicore processors.
Deploy concurrent execution models to supported multicore targets.
Limitations and considerations when partitioning a model for concurrent execution.