This workshop meets twice:

Wednesday, March 15, 1:00-5:00 PM
Thursday, March 16, 1:00-5:00 PM

This 2-day workshop teaches you techniques for training deep neural networks on multi-GPU technology to shorten the training time required for data-intensive applications. Working with deep learning tools, frameworks, and workflows to perform neural network training, you will learn concepts for implementing PyTorch multi-GPUs to reduce the complexity of writing efficient distributed software and to maintain accuracy when training a model across many GPUs.

Workshop format: Interactive presentation with hands-on exercises

Target audience: This workshop is intended for researchers that would like to use multiple GPUs to train deep learning models in PyTorch.

Knowledge prerequisites: Participants should be comfortable with training deep learning models using a single GPU.

Hardware/software prerequisites: Bring a laptop and power cable. All of the hands-on exercises will be done in a web browser on the NVIDIA cloud.

Learning objectives: Participants will learn the theory and practice of training deep learning models using multiple GPUs.