并行和云
使用 Parallel Computing Toolbox™ 在多个 GPU、集群和云中训练深度网络。在本地使用多个 GPU 或在云中扩展深度学习，并以交互方式或批处理作业的形式训练多个网络。要了解有关选项的信息，请参阅Scale Up Deep Learning in Parallel, on GPUs, and in the Cloud。
函数
deep.gpu.deterministicAlgorithms | Set determinism of deep learning operations on the GPU to get reproducible results (自 R2024b 起) |
deep.gpu.fastAttentionAlgorithms | Disable fast attention algorithms used by deep learning operations on the GPU (自 R2026a 起) |
主题
并行、GPU 和云基础
- 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 MATLAB on Multiple GPUs
Speed up deep neural network training using multiple GPUs locally or in the cloud. - Run Experiments in Parallel
Run multiple simultaneous trials or one trial at a time on multiple workers. - Deep Learning with Big Data
Train deep neural networks using large amounts of data. - Resolve GPU Memory Issues
Troubleshoot errors when MATLAB cannot allocate the requested GPU memory.
在云中训练
- Deep Learning in the Cloud
Access MATLAB in the cloud for deep learning. - 在云中使用深度学习数据
将数据上传到云的示例工作流。
- 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.
自定义训练循环
- 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. - Train Network in Parallel with Custom Training Loop
This example shows how to set up a custom training loop to train a network in parallel.
精选示例
使用自动并行支持功能在云中训练网络
此示例说明如何利用 MATLAB® 对并行训练的自动支持来训练卷积神经网络。
使用自动多 GPU 支持训练网络
此示例说明如何使用自动并行支持在本地计算机上使用多个 GPU 进行深度学习训练。
Compare Classification Network Architectures Using Experiment
Train a deep learning network for classification using Experiment Manager.
Compare Dropout Probabilities and Filter Configurations for Image Regression Using Experiment
Train a deep learning network for regression using Experiment Manager.
并行训练深度学习网络
此示例说明如何在本地计算机上运行多个深度学习试验。使用此示例作为模板，您可以修改网络层和训练选项，以满足您的具体应用需要。无论您有一个还是多个 GPU，都可以使用这种方法。如果您只有一个 GPU，网络会在后台逐个进行训练。本示例中的方法使您能够在进行深度学习试验时继续使用 MATLAB®。
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].
将深度学习批处理作业发送到集群
此示例说明如何一边继续在 MATLAB® 中工作或将其关闭，一边在集群中训练深度神经网络。
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.
使用 parfor 训练多个深度学习网络
此示例说明如何使用 parfor 循环对训练选项执行参数扫描。
使用 parfeval 训练多个深度学习网络
此示例说明如何使用 parfeval 对深度学习网络的网络架构深度执行参数扫描，并在训练期间检索数据。
