Scan AI

Scan AI

Deep Learning Institute

Fundamentals of Deep Learning for Multi-GPUs

Join us 2nd June 2022

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.


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.


Time Task
10.00 - 10.15 Introductions
10.15 - 12.00 Principles of Stochastic Gradient Descent (SGD)
12.00 - 13.00 Lunch Break
13.20 - 14.20 Introduction to Distributed Training
14.20 - 14.30 Coffee Break
14.30 - 15.00 Virtualisation of GPUs with Run:AI software
15.00 - 16.15 Algorithmic Challenges of Distributed SGD
16.30 - 16.30 Q&A

Upon completion of the assessment, participants will receive an NVIDIA DLI certificate to recognise their subject matter competency and support professional career growth.

Workshop Details


allow 8 hours (full day)


experience with gradient descent model training

Technologies used

TensorFlow, Keras, Horovod

Assessment Type


Hardware Requirements

Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud


£75 per person

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