Author: Thomas Poppelgaard

Microsoft Azure – NVadsA10 v5-series

Microsoft have released a new instance powered by NVIDIA A10 GPUs and AMD EPYC 74F3V(Milan) CPU with a base frequency of 3.2 Ghz, all cores peak frequency of 4.0Ghz.  With NVadsA10v5-series Azure is introducing virtual machines with partial NVIDIA GPUs. Pick the right sized virtual machine for GPU accelerated graphics applications and virtual desktops starting at 1/6th of a GPU with 4-GiB frame buffer to a full A10 GPU with 24-GiB frame buffer.

The preview is currenty availabe in Azure – US South Central and Azure – West Europe regions.

Prices are now GA (21th March 2022) for North Europe, US East 2, US West3

Sign up for preview to get early access to the NVadsA10v5-series.

NVIDIA Ampere GPU (A10) is supporting GPU-P (SR-IOV) which is why its a big step for partitioning the GPU and making the price dramatically cheaper in Azure. *note there have not been released any prices yet of the instances (its unknown) 

Blogpost last updated: 21th March 2022

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NVIDIA vGPU 14

It’s time to plan updating your NVIDIA Enterprise GPUs. NVIDIA vGPU Software 14 is now GA since February 2022.

NVIDIA vGPU software includes vWSvCS, vPC, and vApps.

If you got any of following NVIDIA GPU’s: A100, A40, A30, A16, A10, A2, RTX A6000, RTX A5000, RTX8000, RTX6000, V100, T4, P100, P40, P6, P4, M60, M10, M6  If you are interested in a quick overview of which NVIDIA enterprise GPU is supporting which hypervisor, Guest os and remoting technology, I highly recommend you check out this link from NVIDIA that provides the NVIDIA vGPU software product support matrix. NVIDIA vGPU software 14 is supported until February 2023. NVIDIA vGPU software 14 is a Product Branch Support. I this article, I am also covering which Public Cloud instance is available with NVIDIA GPUs and which license is BYO or provided by the public cloud provider such as Azure, AWS, GCP, Alibaba. For a list of validated server platforms, refer to NVIDIA vGPU Certified Servers. Important note for EUC (Citrix/VMware customers):
  • NVIDIA vGPU 14.0 is supported with VMware Horizon 2111 (8.4), 2106 (8.3), 2013 (8.2), 2012 (8.1), 2006 (8.0), 7.13, 7.12, 7.11, 7.10, 7.9, 7.8, 7.7, 7.6, 7.5, 7.4, 7.3, 7.2, 7.1, 7.0
  • NVIDIA vGPU 14.0 is only supported with Citrix Virtual Apps & Desktops (LTSR) 7 1912, 7.15 (CR)  7 2112, 7 2109, 7 2106, 7 2103, 7 2012, 7 2009, 7 2003, 7 1909, 7 1906, 7 1903
This release includes the following software:
  • NVIDIA vGPU Manager version 510.47.03 for following hypervisors. (Citrix Hypervisor, VMware vSphere, RHEL KVM)
  • NVIDIA Windows driver version 511.65
  • NVIDIA Linux driver version 510.47.03

New Features in Release 14.0

  • Support for GPUDirect® technology on all C-series vGPUs on GPUs that support SR-IOV
  • Support for a mixture of time-sliced vGPUs of the same frame buffer size on the same GPU
  • Support for Tesla Compute Cluster (TCC) mode for Q-series vGPUs on Windows guest VMs
  • Support for GPU System Processor (GSP) in GPU pass through and bare-metal configurations on Linux with vCS
    Note: If you are using a product other than vCS, you must disable GSP as explained in Virtual GPU Software User Guide.
  • Enhanced NVIDIA CUDA Toolkit support:
    • NVIDIA CUDA Toolkit profilers can be enabled when unified memory is enabled.
    • Nsight Systems GPU context switch trace is supported.
  • Enhancements to the NVIDIA Management Library (NVML) to determine whether a vGPU type supports GPUDirect technology and peer-to-peer CUDA transfers over NVLink
  • Addition of RPM and Debian packages for the NVIDIA vGPU software graphics drivers for Linux
  • Security updates – see Security Bulletin: NVIDIA GPU Display Driver – February 2022, which is posted shortly after the release date of this software and is listed on the NVIDIA Product Security pages
  • Miscellaneous bug fixes

Hardware and Software Support Introduced in Release 14.0

  • Support for the following GPUs:
    • NVIDIA A2
    • NVIDIA A30X
    • NVIDIA A100X
  • Support for Red Hat Enterprise Linux with KVM hypervisor 8.5
  • Support for Red Hat Enterprise Linux 8.5 as a guest OS
  • Support for Debian 10 as a guest OS
  • Support for Citrix Virtual Apps and Desktops version 7 2112
  • Support for VMware Horizon 2111 (8.4)

Feature Support Withdrawn in Release 14.0

  • Red Hat Enterprise Linux with KVM hypervisor 8.1, 7.8, and 7.7 are no longer supported.
  • Red Hat Enterprise Linux 8.1 is no longer supported as a guest OS.
  • Red Hat Enterprise Linux 7.8 and 7.7 are no longer supported as a guest OS.
  • Windows Server 2012 R2 is no longer supported as a guest OS.

Features Deprecated in Release 14.0

The following table lists features that are deprecated in this release of NVIDIA vGPU software. Although the features remain available in this release, they might be withdrawn in a future release. In preparation for the possible removal of these features, use the preferred alternative listed in the table.

Deprecated Feature Preferred Alternative Additional Information
Legacy NVIDIA vGPU software license server NVIDIA License System NVIDIA Virtual GPU Software License Server End of Life Notice

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Findings Video conference with Azure Virtual Desktop using Teams

Introduction

Over the last couple of years, there has been an impressive flux with many businesses and institutions adopting and relying on large-scale remote working and remote learning environments to maintain workforce and learning continuity. During this time, it’s generally been recognised that this type of remote working/learning has been quite successful, with many businesses and institutions continuing remoting working/learning practices or introducing hybrid models with a combination of remote and office work for their staff. 

One of the reasons why remote working/learning has been successful is the availability of supporting technologies that have delivered a high standard of human communication and engagement across large numbers of workers or students/faculty in remote environments. Video conferencing applications, which includes video conferencing, screen sharing, IMs and more, are such technologies that have contributed to viable remote working/learning environment success.  

But to use these applications to their fullest potential, a robust IT infrastructure is also a must. Many large enterprise companies, as well as SMB and other institutions have centralised their IT environment into virtualized desktop infrastructure (VDI), either as an on-premises solution or as a managed-service by cloud service providers (CSP). Centralizing resources, applications and data into a single infrastructure allows for better IT management and security of vital resources and data which can help improve workforce productivity, data security and IT efficiencies.

Investigation overview

This blog details a recent technical investigation where popular video conferencing applications are deployed on AMD-based Azure instances to determine the performance of each application, the number of deployable users in a multi-session environment, and the user experience each person would receive. The AMD-based instances includes both CPU-only based instances and CPU+GPU based instances to understand the impact of GPU-enabled resources to the density and experience of the users.

So next let’s look at the various parameters for the investigation.  

The Lab: 

For the investigation, we had three areas of consideration: 

   This image has an empty alt attribute; its file name is image-5.png
1) Azure session host 2) Application3) End-point devices

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Findings Video conference with Azure Virtual Desktop using Meet

 

 

Introduction

Over the last couple of years, there has been an impressive flux with many businesses and institutions adopting and relying on large-scale remote working and remote learning environments to maintain workforce and learning continuity. During this time, it’s generally been recognised that this type of remote working/learning has been quite successful, with many businesses and institutions continuing remoting working/learning practices or introducing hybrid models with a combination of remote and office work for their staff. 

One of the reasons why remote working/learning has been successful is the availability of supporting technologies that have delivered a high standard of human communication and engagement across large numbers of workers or students/faculty in remote environments. Video conferencing applications, which includes video conferencing, screen sharing, IMs and more, are such technologies that have contributed to viable remote working/learning environment success.  

But to use these applications to their fullest potential, a robust IT infrastructure is also a must. Many large enterprise companies, as well as SMB and other institutions have centralised their IT environment into virtualized desktop infrastructure (VDI), either as an on-premises solution or as a managed-service by cloud service providers (CSP). Centralizing resources, applications and data into a single infrastructure allows for better IT management and security of vital resources and data which can help improve workforce productivity, data security and IT efficiencies.

Investigation overview

This blog details a recent technical investigation where popular video conferencing applications are deployed on AMD-based Azure instances to determine the performance of each application, the number of deployable users in a multi-session environment, and the user experience each person would receive. The AMD-based instances includes both CPU-only based instances and CPU+GPU based instances to understand the impact of GPU-enabled resources to the density and experience of the users.

So next let’s look at the various parameters for the investigation.  

The Lab: 

For the investigation, we had three areas of consideration: 

   This image has an empty alt attribute; its file name is image-5.png
1) Azure session host 2) Application3) End-point devices

Continue reading

Findings Video conference with Azure Virtual Desktop using Zoom

 

 

 

Introduction

Over the last couple of years, there has been an impressive flux with many businesses and institutions adopting and relying on large-scale remote working and remote learning environments to maintain workforce and learning continuity. During this time, it’s generally been recognised that this type of remote working/learning has been quite successful, with many businesses and institutions continuing remoting working/learning practices or introducing hybrid models with a combination of remote and office work for their staff. 

One of the reasons why remote working/learning has been successful is the availability of supporting technologies that have delivered a high standard of human communication and engagement across large numbers of workers or students/faculty in remote environments. Video conferencing applications, which includes video conferencing, screen sharing, IMs and more, are such technologies that have contributed to viable remote working/learning environment success.  

But to use these applications to their fullest potential, a robust IT infrastructure is also a must. Many large enterprise companies, as well as SMB and other institutions have centralised their IT environment into virtualized desktop infrastructure (VDI), either as an on-premises solution or as a managed-service by cloud service providers (CSP). Centralizing resources, applications and data into a single infrastructure allows for better IT management and security of vital resources and data which can help improve workforce productivity, data security and IT efficiencies.

Investigation overview

This blog details a recent technical investigation where popular video conferencing applications are deployed on AMD-based Azure instances to determine the performance of each application, the number of deployable users in a multi-session environment, and the user experience each person would receive. The AMD-based instances includes both CPU-only based instances and CPU+GPU based instances to understand the impact of GPU-enabled resources to the density and experience of the users.

So next let’s look at the various parameters for the investigation.  

The Lab: 

For the investigation, we had three areas of consideration: 

  This image has an empty alt attribute; its file name is image-1.png This image has an empty alt attribute; its file name is image-5.png
1) Azure session host 2) Application3) End-point devices

Continue reading