Parallel Computing Toolbox


Parallel Computing Toolbox

Perform parallel computations on multicore computers, GPUs, and clusters

Speed Up MATLAB with Multicore Computers

Use parfor and other features to execute parallel MATLAB threads or processes for tasks such as parameter sweeps, optimizations, and Monte Carlo simulations. Let MATLAB language features (with Parallel Computing Toolbox) handle resources, file dependencies, and other details—enabling you to focus on your work.

Accelerate MATLAB with GPUs

You can use NVIDIA® GPUs without having to write any additional code, so you can focus on your applications rather than performance tuning. Key functions in MATLAB, Simulink, and several add-on products, such as Deep Learning Toolbox, have GPU enabled functions. Advanced developers can also create MEX functions containing CUDA code. Use multiple GPUs on desktop, compute clusters, and cloud environments.

Additional Parallel-Enabled MATLAB Functionality

Many features in MATLAB and add-on products have automatic parallel support, and many apps have enabled parallel features. Parallel Computing Toolbox includes an extensive parallel language covering execution models from parallel function execution to data parallelism without needing to recode your algorithm.

Run Multiple Simulink Simulations in Parallel

Use the parsim function to run your simulations in parallel. The function distributes multiple simulations to multicore CPUs to speed up overall simulation time. parsim also automates the creation of parallel pools, identifies file dependencies, and manages build artifacts, so that you can focus on your design work. You can execute parallel simulations interactively or in batch.

Simulation Manager

Simulation manager is integrated with parsim and can be used to monitor and visualize multiple simulations in one window. You can select an individual simulation and view its specifications, as well as use the Simulation Data Inspector to examine simulation results. You can also conveniently run diagnostic tasks or abort simulations.

Use Parallel-Enabled Simulink Functionality

In addition to using parsim and batchsim functions to run Simulink simulations, there are many add-on products for Simulink, including Simulink Design Optimization, Reinforcement Learning Toolbox, Simulink Test, and Simulink Coverage that provide parallel capability for running simulations in parallel without writing any code.

Run a MATLAB Desktop in Public and Private Clouds

Speed up analysis and simulations by taking advantage of on-demand, high-performance CPU and GPU machines available in the cloud. Run MATLAB and Simulink directly on virtual machines in the Amazon Web Services® (AWS) environment or in Microsoft Azure®.

Scale to Clusters with MATLAB Parallel Server

Develop a prototype on your desktop and scale to a compute cluster or clouds without recoding. Access different execution environments from your desktop just by changing your cluster profile. 

Use Distributed Arrays on MATLAB Parallel Server

Execute calculations that will not fit in the memory of a single machine without needing to recode your algorithm. Use the many functions that can run automatically as distributed computations when called with a distributed array input. Prototype on your desktop and scale up to additional resources using MATLAB Parallel Server for full-scale execution.

“We used Parallel Computing Toolbox with MATLAB Parallel Server to distribute the work on a 56-processor cluster. This enabled us to rapidly identify an optimal neural network configuration using MATLAB and Deep Learning Toolbox, train the network using data from the transplantation databases, and then run simulations to analyze risk factors and survival rates.”

Dr. Johan Nilsson, Skåne University Hospital, Lund University

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