Parallel and Cloud
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, on GPUs, and in the Cloud.
- Scale Up Deep Learning in Parallel, on GPUs, and in the Cloud
Explore options for deep learning with MATLAB® in parallel and using multiple GPUs, locally or in the cloud.
- Deep Learning with Big Data
Train deep neural networks using large amounts of data.
- Use Experiment Manager to Train Networks in Parallel
Run multiple simultaneous trials or one trial at a time on multiple workers. (Since R2020b)
- Deep Learning with MATLAB on Multiple GPUs
Speed up deep neural network training using multiple GPUs locally or in the cloud.
- Run Custom Training Loops on a GPU and in Parallel
Speed up custom training loops by running on a GPU, in parallel using multiple GPUs, or on a cluster.
- Resolve GPU Memory Issues
Troubleshoot errors when MATLAB cannot allocated the requested GPU memory
- Deep Learning in the Cloud
Access MATLAB in the cloud for deep learning.
- Work with Deep Learning Data in the Cloud
Example workflows for uploading data to the cloud.
- Cloud AI Workflow Using the Deep Learning Container
An example workflow for training, importing data, and optimizing a deep neural network in the cloud using the Deep Learning Container.