Parallelverarbeitung und Cloud
Trainieren Sie tiefe Netze auf mehreren Grafikkarten, Clustern und Clouds mithilfe von Parallel Computing Toolbox™. Skalieren Sie Deep Learning mit mehreren Grafikkarten lokal oder auf Clustern und trainieren Sie mehrere Netze interaktiv oder in Batch-Jobs Informationen zu den Optionen finden Sie unter Scale Up Deep Learning in Parallel, on GPUs, and in the Cloud.
Themen
- 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.
- Run Experiments in Parallel
Run multiple simultaneous trials or one trial at a time on multiple workers.
- 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 allocate 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 MathWorks Cloud Center
Example workflows for training, importing data, and optimizing a deep neural network in the cloud using MathWorks Cloud Center.
- Cloud AI Workflow Using the Deep Learning Container
Example workflows for training, importing data, and optimizing a deep neural network in the cloud using the Deep Learning Container.
Enthaltene Beispiele
Train Network in the Cloud Using Automatic Parallel Support
Train a convolutional neural network using MATLAB® automatic support for parallel training.
Train Network Using Automatic Multi-GPU Support
Use multiple GPUs on your local machine for deep learning training using automatic parallel support.
Create a Deep Learning Experiment for Classification
Train a deep learning network for classification using Experiment Manager.
Create a Deep Learning Experiment for Regression
Train a deep learning network for regression using Experiment Manager.
Train Deep Learning Networks in Parallel
Run multiple deep learning experiments on your local machine. Using this example as a template, you can modify the network layers and training options to suit your specific application needs. You can use this approach with a single or multiple GPUs. If you have a single GPU, the networks train one after the other in the background. The approach in this example enables you to continue using MATLAB® while deep learning experiments are in progress.
Use parfor to Train Multiple Deep Learning Networks
Use a parfor loop to perform a parameter sweep on a training option.
Use parfeval to Train Multiple Deep Learning Networks
Use parfeval to perform a parameter sweep on the depth of the network architecture for a deep learning network and retrieve data during training.
Work with Deep Learning Data in AWS
Upload data to an Amazon S3™ bucket.
Work with Deep Learning Data in Azure
Set up, write to, and read from Azure® Blob Storage.
Train Network in Parallel with Custom Training Loop
Set up a custom training loop to train a network in parallel.
Train Network Using Federated Learning
Train a network using federated learning. Federated learning is a technique that enables you to train a network in a distributed, decentralized way [1].
Use batch to Train Multiple Deep Learning Networks
Train multiple networks in batch jobs using a cluster so that you can continue working or close MATLAB® during training.
Train Network on Amazon Web Services Using MATLAB Deep Learning Container
Train a deep learning network in the cloud using MATLAB® on an Amazon EC2® instance.
Use Amazon S3 Buckets with MATLAB Deep Learning Container
Train your deep learning model with training data stored in an Amazon S3™ Bucket and save the trained model to the cloud.
Use Experiment Manager in the Cloud with MATLAB Deep Learning Container
Fine-tune your deep learning network by using Experiment Manager in the cloud. Make use of multiple NVIDIA® high-performance GPUs on an Amazon EC2® instance to run multiple experiments in parallel. Tune the hyperparameters of your network and try different network architectures. You can sweep through a range of hyperparameters automatically and save the results for each variation. Compare the results of your experiments to find the best network.
