Optimizing Simulation Performance in Simulink
C-COR
With Simulink and Parallel Computing Toolbox on an eight-node cluster, we ran eight simulations in the same time that it takes to do one. This enabled us to run hundreds of simulations to find the best filter topology and values, leading to a 10-15 dB performance improvement.
- Parallel Computing Overview
- Solving Large Problems with MATLAB
- Optimizing Simulation Performance in Simulink
- Managing Parallel Computing Products in Your IT Environment
Run Multiple Simulations at the Same Time
System design and testing often require engineers to run their Simulink models over multiple design configurations and operating conditions to improve and verify the design. Using MathWorks parallel computing products, you can exploit the repetitive nature of activities such as Monte Carlo simulations and design optimization studies by distributing work across multicore desktops and computer clusters.
Built-in parallel computing capabilities in many MathWorks products let you take advantage of parallel computing with little or no programming.
Generate Code in Parallel for Referenced Models
By using Parallel Computing Toolbox on a multicore desktop or MATLAB Distributed Computing Server on a computer cluster, you can speed up code generation builds for Simulink models that contain large model reference hierarchies. You can use this capability to reduce diagram update times for simulation when the referenced models are in accelerated mode, and also for generating C/C++ code used for deployment to a DSP or microcontroller.
Free Parallel Computing Interactive Kit
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