Parallel Computing Toolbox™ lets you solve computationally and data-intensive problems using multicore processors, GPUs, and computer clusters. High-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms—let you parallelize MATLAB® applications without CUDA or MPI programming. You can use the toolbox with Simulink® to run multiple simulations of a model in parallel.
The toolbox lets you use the full processing power of multicore desktops by executing applications on workers (MATLAB computational engines) that run locally. Without changing the code, you can run the same applications on a computer cluster or a grid computing service (using MATLAB Distributed Computing Server™). You can run parallel applications interactively or in batch.
Distribute computations across available parallel computing resources, and speed up your analysis or simulation tasks.Learn more
Run MATLAB workers locally on your multicore desktop to execute your parallel applications.Learn more
Execute parallel applications interactively and in batch.Learn more
Discover more about Parallel Computing Toolbox by exploring these resources.
Explore documentation for Parallel Computing Toolbox functions and features, including release notes and examples.
Browse the list of available Parallel Computing Toolbox functions.
View system requirements for the latest release of Parallel Computing Toolbox.
View articles that demonstrate technical advantages of using Parallel Computing Toolbox.
Read how Parallel Computing Toolbox is accelerating research and development in your industry.
Find answers to questions and explore troubleshooting resources.
Run computationally intensive MATLAB programs and Simulink models on computer clusters, clouds, and grids.
Learn about installing and configuring MATLAB Distributed Computing Server.
Get started learning Parallel Computing Toolbox.
Parallel Computing Toolbox requires MATLAB.
Use Parallel Computing Toolbox to solve scientific and engineering challenges: