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Analyze and Optimize Simulation Multicore Execution for Simulink Models Using Dataflow
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Learn how to perform multicore analysis to optimize simulation performance of your Simulink® models using the dataflow domain.
In this example, we will use a model that simulates acoustic beamforming on a uniform linear array (ULA) of microphones and show how to:
- Optimize model settings for simulation performance
- Provide multicore analysis constraints, such as maximum number of threads and multithreading threshold
- Run multicore analysis to profile simulation execution times of blocks and automatically assign blocks to threads to improve simulation performance
- Visualize analysis results and investigate additional multicore diagnostics
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© 2022 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
In this example, we will use a model that simulates acoustic beamforming on a uniform linear array (ULA) of microphones and show how to:
- Optimize model settings for simulation performance
- Provide multicore analysis constraints, such as maximum number of threads and multithreading threshold
- Run multicore analysis to profile simulation execution times of blocks and automatically assign blocks to threads to improve simulation performance
- Visualize analysis results and investigate additional multicore diagnostics
--------------------------------------------------------------------------------------------------------
© 2022 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
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