Scan AI

Fundamentals of Deep Learning for Multi-GPUs

Instructor Led Workshop

This 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’ll learn concepts for implementing Horovod multi-GPUs to reduce the complexity of writing efficient distributed software and to maintain accuracy when training a model across many GPUs.

Objectives

At the conclusion of the workshop, you’ll have an understanding of Stochastic Gradient Descent (SGD) - a crucial tool in parallelised training; batch size and its effect on training time and accuracy; transforming a single-GPU implementation to a Horovod multi-GPU implementation and techniques for maintaining high accuracy when training across multiple GPUs.