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Virtualized GPU Instances on Dell EMC PowerEdge

Platforms for Compute Intensive Workloads

AI adoption is growing in many organizations leading to increased

demand of GPU accelerated compute instances. We explore how

IT teams can leverage existing investment in virtualized

infrastructure combined with NVIDIA Virtual GPU software to

provide optimized and secure GPU-ready compute environments

for AI researcher and engineers.

Motivation for GPU Virtualization

The requirement and demand for GPU accelerated compute

instances is steadily rising in all organizations, driven primarily by

rise of AI and Deep Learning (DL) techniques to realize increased

efficiencies and improve customer interactions. IT environments

continue to adopt virtualization to run all workloads and address

requirements of providing secure and agile compute capabilities to

end users. NVIDIA Virtual GPU software (previously referred to as

GRID) enables virtualizing a physical GPU and allows it to be

shared across multiple virtual machines. The rising demand for

GPU accelerated compute instances can be achieved by

virtualizing GPUs and deploying cost effective GPU accelerated

VM instances. Enabling a centralized and hosted solution in the

data center provides the security and scalability that is critical to

enterprise customers.

NVIDIA Virtual GPU

software enables virtual

GPUs to be created on a

Dell EMC server with

NVIDIA GPUs that can be

shared across multiple

virtual machines. Better

utilization and sharing are

achieved by transforming

a one-to-one relationship

from GPU to user to one-

to-many.

Tech Note by

Ramesh Radhakrishnan

Janet Morss

Mike Bennett

Matt Ogle

Summary

In this DfD we address a

common problem that is

faced by IT teams across

different organizations –

being able to efficiently

share and utilize NVIDIA

GPU resources across

different teams and

projects.

Figure 1. GPU enabled VM instances using GPU

Pass-Though and GPU Virtualization (vGPU)

Summary of content (5 pages)

PAGE 1
Direct from Development Server and Infrastructure Engineering Virtualized GPU Instances on Dell EMC PowerEdge Platforms for Compute Intensive Workloads Tech Note by Ramesh Radhakrishnan Janet Morss Mike Bennett Matt Ogle AI adoption is growing in many organizations leading to increased demand of GPU accelerated compute instances.
PAGE 2
Copyright © 2020 Dell Inc. or its subsidiaries. All Rights Reserved. Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries Traditionally, the IT best practices for compute-intensive (non-graphical) VM instances leveraged GPU pass-through shown in the left half of Figure 1. In a VMware environment, this is referred to as the VM DirectPath I/O mode of operation. It allows the GPU device to be accessed directly by the guest operating system, bypassing the ESXi hypervisor.
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Copyright © 2020 Dell Inc. or its subsidiaries. All Rights Reserved. Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries Figure 2. GPU enabled VM instances using GPU PassThough and GPU Virtualization (vGPU) NVIDIA GPU Virtualization software transforms a physical GPU installed on a server to create virtual GPUs (vGPU) that can be shared across multiple virtual machines.
PAGE 4
Copyright © 2020 Dell Inc. or its subsidiaries. All Rights Reserved. Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries The different editions of the vGPU driver are described next. NVIDIA virtual GPU Software is available in four editions that deliver accelerated virtual desktops to support the needs of different workloads.
PAGE 5
Copyright © 2020 Dell Inc. or its subsidiaries. All Rights Reserved. Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries vComputeServer Features and Deployment Patterns vComputeServer was designed to complement existing GPU virtualization capabilities for graphics and VDI and address the needs of the data centers to virtualize compute-intensive workloads such as AI, DL and HPC.