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.

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.

Agenda

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

Duration

allow 8 hours (full day)

Prerequisites

experience with gradient descent model training

Technologies used

TensorFlow, Keras, Horovod

Assessment Type

Code-based

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

Cost

£75 per person

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