Why would you need to have a GPU for machine learning (ML) and high performance computing (HPC) platforms? What are GPUs used for? How can I leverage GPU technology with VMware vSphere? What do I need to do to expose GPU devices to my machine learning workloads? How can I cater to the need for a flexible and highly performant infrastructure of my data scientists?

If those are some of the questions you are struggling with, look no further. This learning guide will go into details on using GPUs for machine learning with VMware vSphere.

Download the Free Learning Guide

Make sure you download your complimentary copy of the “Learning Guide – GPUs for Machine Learning on VMware vSphere” right here. This guide contains extensive information on why GPU’s are the preferred hardware accelerator with types of computations used by machine learning. It also details on the architecture of a GPU and how to configure vSphere to connect GPU devices to your workloads. We’ll do so using three different, though complementary usage scenarios.

Learning Guide - GPUs for Machine Learning on VMware vSphere

Happy reading!

-Justin Murray and Niels Hagoort

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About the Author

Niels Hagoort

Niels Hagoort is a Technical Marketing Architect and VCDX #212 working for VMware in the Cloud Platform Business Unit. In his role, he covers the vSphere ESXi architecture including hardware (accelerators) and compatibility, core storage, networking and resource management. Find created content at and Find Niels on twitter via @NHagoort.