Nvidia “NGC” Deep Learning Containers

Chetan Tekur and Fraser Gardiner, Nvidia

Abstract: 

This tutorial will cover the Nvidia’s “NGC” containers for deep learning including: which Deep Learning Frameworks and utilities are provided in Nvidia NGC containers; how to access and use these containers; which GPUs and cloud services can run Nvidia NGC containers; sample and example code included in Nvidia NGC containers which implement Deep Learning models; latest features to simplify achieving optimum performance and support for multi-node training.

Chetan Tekur, Nvidia

Chetan Tekur is a field applications engineer and solutions architect at Nvidia, where he's focused on CSP and networking customers. Chetan has 11+ years of experience in HW industry focusing on pre-sales/post-sales support, technology evangelization, and customer management. He has a Master’s degree in Electrical Engineering from NC State University.

Fraser Gardiner, Nvidia

Fraser Gardiner is the Solutions Architecture Director that supports Nvidia’s Major Cloud Service Provider Partners. He has over 25 years of experience in Unix/Linux systems to support both mission-critical enterprise applications as well as industrial/hyperscale use cases. He has held senior technical or technical leadership roles at Apple, HP, and Oracle/Sun Microsystems.
BibTeX
@conference {232999,
author = {Chetan Tekur and Fraser Gardiner},
title = {Nvidia {\textquotedblleft}NGC{\textquotedblright} Deep Learning Containers},
year = {2019},
address = {Santa Clara, CA},
publisher = {{USENIX} Association},
month = may,
}