并行和云
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
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。
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.