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Introduction

The NVIDIA® T4 GPU, based on the latest NVIDIA Turing™ architecture, is now supported for virtualization workloads. The NVIDIA virtual GPU solution, with VMware vSphere, can be deployed with T4 – the most universal GPU to date – capable of running any workload to drive greater data center efficiency. This is because the same GPU computing platform used by designers and engineers to design the chairs you sit on, the shoes you’re wearing and the cars you drive is also enabling artists to create photorealistic imagery, by providing the computation required to allow light to bounce off surfaces and look just as they would in real life via real-time ray tracing. This computing platform also enables AI-enhanced graphics, video and image processing to speed creative workflows and tensor cores to accelerate deep learning inferencing workloads. And as the modern digital workplace becomes more graphics intensive, this computing platform can also be used to provide a native-PC user experience to meet the growing needs of virtualized office productivity applications. This universal GPU accelerator, coupled with technologies like support for VMware vMotion of GPU accelerated VMs, provide the ultimate flexibility as organizations cost-effectively scale VDI.

Watch this on-demand webinar as we walked through T4 benchmarks, its positioning within the Tesla GPU family, and demonstrated its advantages for a wide range of virtualization workloads.

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DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.

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Speaker

Varun Nanda Kumar

Virtual GPU Product Manager, NVIDIA

Varun is a Product Manager for NVIDIA Virtual GPU (vGPU) technology where he manages the product lifecycle and OEM relationships for the vGPU solution. With a Masters of Engineering Management from Dartmouth, Varun enjoys working in a fast-paced, ever changing environment and has had the opportunity to work on strategic projects across various industries.

Emily Apsey

NVIDIA Performance Engineer, NVIDIA

Emily Apsey is Performance Engineering for NVIDIA Virtual GPU (vGPU) technology where she oversees benchmarking for the vGPU solution. Emily works closely with technology from OEM, hypervisor, and ISV partners to understand the performance and scalability of applications in virtualized environments. Emily continuously analyzes performance during the fast-paced product launch lifecycle, and enjoys doing technical deep dives into new and ever changing technology.

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Date & Time: Wednesday, April 22, 2018