Train deep networks on multiple GPUs, clusters, and clouds, using Parallel Computing Toolbox™. Scale up deep learning with multiple GPUs locally or on clusters, and train multiple networks interactively or in batch jobs. To learn about options, see Scale Up Deep Learning in Parallel and in the Cloud.
Train deep networks on CPUs, GPUs, clusters, and clouds, and tune options to suit your hardware.
Options for deep learning with MATLAB using multiple GPUs, locally or in the cloud.
Specify multiple GPUs to use locally or in the cloud for training.
This example shows how to use multiple GPUs on your local machine for deep learning training using automatic parallel support.
This example shows how to run multiple deep learning experiments on your local machine.
This example shows how to use a
parfor loop to perform a parameter sweep on a training option.
This example shows how to use
parfeval to perform a parameter sweep on the depth of the network architecture for a deep learning network and retrieve data during training.
This example shows how to upload data to an Amazon S3 bucket.
This example shows how to send deep learning training batch jobs to a cluster so that you can continue working or close MATLAB during training.