Concept Guide
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Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries
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. This provides a level of performance of a
GPU on vSphere that is very close to its performance on a native system (within 4-5%).
The main reasons for using the passthrough approach to expose GPUs on vSphere are:
(i) Simplicity: It is straightforward to allocate GPUs to a VM using pass-though and offer GPU
acceleration benefits to end users
(ii) Dedicated use: there is no need for sharing the GPU among different VMs, because a single
application will consume one or more full GPUs
(iii) Replicate public cloud instances: public cloud instances use GPU pass-through, and end
user wants the same environment in an on-premises datacenter
(iv) A single virtual machine can make use of multiple physical GPUs in passthrough mode
An important point to note is that the passthrough option for GPUs works without third-party software
driver being loaded into the ESXi hypervisor.
Disadvantages of GPU passthrough is as follows:
(i) The entire GPU is dedicated to that VM and there is no sharing of GPUs amongst the VMs
on a server.
(ii) Advanced vSphere features of vMotion, Distributed Resource Scheduling (DRS) and
Snapshots are not allowed with this form of using GPUs with a virtual machine.
Overview of NVIDIA vGPU Platform
GPU virtualization (NVIDIA vGPU) addresses limitations of pass-through but was traditionally
deployed to accelerate virtualized profession graphics applications, virtual desktop instances or
remote desktop solutions. NVIDIA added support for AI, DL and high-performance computing (HPC)
workloads in GRID 9.0 that was released in summer 2019. It also changed vGPU licensing to make
it more amenable for compute use cases. GRID vPC/vApps and Quadro vDWS are licensed by
concurrent user, either as a perpetual license or yearly subscription. Since vComputeServer is for
server compute workloads, the license is tied to the GPU rather than a user and is therefore licensed
per GPU as a yearly subscription. For more information about NVIDIA GRID software, see
http://www.nvidia.com/grid.
Figure 2 shows the different components of the Virtual GPU software stack.