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멀티코어 프로세서 타깃

멀티코어 또는 FPGA 시스템에 배포하도록 설계된 시스템에 대한 동시 실행 모델링

멀티코어 프로그래밍, 즉 동시 실행을 위한 모델링을 통해 멀티코어 프로세서 및 멀티프로세서 시스템에 배포할 동시성 시스템을 손쉽게 만들 수 있습니다. 이러한 시스템의 예로는 신호 처리 시스템 및 플랜트 제어 시스템이 있습니다. Simulink^® 분할 및 매핑 기법을 사용하면 동시 실행을 위한 시스템 설계에서 일반적으로 발생하는 문제를 해결할 수 있습니다.

다음 그림은 CPU 및 FPGA 기반 멀티프로세서 시스템에서 실행되도록 설계된 여러 함수가 포함된 샘플 시스템을 보여줍니다. 이 시스템은 CPU 태스크 스케줄러 또는 FPGA에 매핑된 여러 컴포넌트로 분할됩니다.

멀티코어 프로그래밍의 기본 사항은 Concepts in Multicore Programming 항목을 참조하십시오. Simulink에서 동시 실행되도록 시스템을 설계하는 방법에 대한 자세한 내용은 Multicore Programming with Simulink 항목을 참조하십시오.

함수

`Simulink.architecture.config`	Create or convert configuration for concurrent execution
`Simulink.architecture.add`	Add tasks or triggers to selected architecture of model
`Simulink.architecture.delete`	Delete triggers and tasks from selected architecture of model
`Simulink.architecture.find_system`	Find objects under architecture object
`Simulink.architecture.get_param`	Get configuration parameters of architecture objects
`Simulink.architecture.importAndSelect`	Import and select target architecture for concurrent execution environment for model
`Simulink.architecture.profile`	Generate profile report for model configured for concurrent execution
`Simulink.architecture.register`	Add custom target architecture to concurrent execution target architecture selector
`Simulink.architecture.set_param`	Set architecture object properties

객체

Simulink.GlobalDataTransfer Configure concurrent execution data transfers

툴

동시 실행 툴

Specify tasks, triggers, and nodes for concurrent execution of Simulink model

도움말 항목

Simulink의 멀티코어 프로그래밍 이해

Concepts in Multicore Programming
Theory relevant to modeling for concurrent execution.
Multicore Programming with Simulink
Modeling for concurrent execution using Simulink.
Implicit and Explicit Partitioning of Models
Learn about the key differences between implicit and explicit partitioning.
Supported Targets for Multicore Programming
Deploy concurrent execution models to supported multicore targets.
Limitations with Multicore Programming in Simulink
Limitations and considerations when partitioning a model for concurrent execution.

모델 구성

Configure Your Model for Concurrent Execution
Learn how to configure your Simulink model to take advantage of concurrent execution.
Specify a Target Architecture
Choose or define a target architecture for a model configured for concurrent execution.
Partition Your Model Using Explicit Partitioning
Add tasks, create partitions, and map individual tasks to partitions using explicit partitioning.
Configure Data Transfer Settings Between Concurrent Tasks
Specify options for handling data transfers between concurrently executing partitions.

Simulink에서 병렬 처리 구현

Implement Data Parallelism in Simulink
This example shows how to implement data parallelism for a system in a Simulink model.
Implement Task Parallelism in Simulink
This example shows how to implement task parallelism for a system represented in a Simulink® model.
Implement Pipelining in Simulink
This example shows how to implement pipelining for a system represented in a Simulink® model.

코드 생성

Optimize and Deploy on a Multicore Target
Configure a model for concurrent execution using explicit partitioning and deploy it to a target.
Assign Tasks to Cores for Multicore Programming
This example shows how to take advantage of executing code on a multicore processor by graphical partitioning.

추천 예제

Assign Tasks to Cores for Multicore Programming

Take advantage of executing code on a multicore processor by graphical partitioning. This example requires Simulink® Coder™ software to generate multithreaded code.

예제 열기

Implement an FFT on a Multicore Processor and an FPGA

Take advantage of a multicore processor target with FPGA acceleration by graphically partitioning a model. This example requires Simulink Coder™ to generate multi-threaded code and HDL Coder™ to generate HDL code. You cannot generate HDL code on Macintosh systems.

모델 열기

Multicore Programming of a Field-Oriented Control on Zynq

Demonstrates how to implement a control algorithm that contains multiple rates on Zynq®. To take advantage of both the cores and the FPGA hardware, the example uses a graphical partitioning approach such that code from different partitions is distributed across the cores and the hardware.

모델 열기

Multicore Deployment of a Plant Model

Illustrates how to take advantage of executing multithreaded code on a multicore processor using graphical partitioning. This example requires Simulink® Coder™ to generate multithreaded code.

모델 열기

Modeling Objects with Identical Dynamics Using For Each Subsystem

Model multiple objects with identical dynamics using the For Each subsystem. The number of objects is parameterized by the length of the input signal.