Parallel and Distributed Computing with MATLAB


Using the Parallel Computing capabilities in MATLAB allows users to take advantage of additional hardware resources that may be available either locally on their desktop or on clusters, clouds, and grids. By using more hardware, you can reduce the cycle time for your workflow and solve computationally and data-intensive problems faster. In this webinar, we will discuss a range of workflows available to scale MATLAB applications with minimal changes to your MATLAB code and without needing to learn low-level programming.


  • Leveraging multiple cores or CPUs
  • Working with high-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms.
  • Scaling up to utilize clusters, grids and clouds
  • Utilizing tall and distributed arrays to work with large data sets
  • Using MATLAB for GPU computing

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