Tag: NVIDIA GRID

NVIDIA GRID – AppGuide (REVIT)

Hi All.

I want to share this with you all, Luke Wignall and his team from NVIDIA have created some great AppGuides, that helps with understanding how many users can you put on a NVIDIA GRID system with either K1/K2 in a VMware environment. These guides are made together with vendors such as Autodesk. The guides focus on following apps Autodesk Revit.

In this blogpost my goal is to highlight the great work NVIDIA have done creating the scalability app guides and these guides helps you if you want to virtualize Autodesk Revit with NVIDIA GRID and VMware Horizon. The guides are great – cause they give an idea what you would require in a virtualized environment and these can be reused for other virtualized platforms such as Citrix and Microsoft – keep in mind that results might be different. If you would like to get more informations about how the setup is configured and which methodology i recommend you read the AppGuide, you can download it in under source in the end of this article.

The appguides gives a great idea to understand the impact of CPU and how the GPU are giving value.

About Autodesk Revit 2015

Autodesk Revit is Building Information Modeling (BIM) software with features for architectural design, MEP and structural engineering, and construction. Revit requires a GPU as you rotate, zoom, and interact with drawings. It also creates heavy CPU load as it manages all the elements of a drawing via a database, which means we need high performance storage as well. The heaviest Revit CPU usage occurs during data-rich operations like file open/save and model updates. As a result both CPU and GPU need to be considered in architecting your vGPU solution. The size of your drawing file, the concurrency of your users, and the level of interaction with 3D data need to be factored into defining your user groups.

Results Appguide for Autodesk Revit 2015

The following are results of our testing, looking for the greatest scalability while still within performance expectations. Its important to note that your users, your data, and your hardware, will impact these results and you may decide a different level of performance or scalability is required to meet your individual business needs. As the RFO Benchmark does not currently exercise some of Revit’s newest GPU capabilities, and was built to push the limits of dedicated hardware versus the shared resources of VDI, the decision was made to stop testing once the host’s CPU was approaching 100% utilized and test times had climbed past twice what we were finding on the a single physical workstation with dedicated resources. We then met with the Autodesk Revit team, discussed the results, reviewed the tests in action, and determined with eyes on that this was still within what a typical user would deem acceptable and usable. It’s been well documented that storage performance is key to providing high performance graphics workloads, especially with many users and ever-growing file or model sizes.

FYI – Lower scores are better, representing less time to perform the activity in below tables.

results with Intel Ivy Bridge processors & NVIDIA GRID K2 (K220Q GPU Profile)

results with Intel Ivy Bridge processors & NVIDIA GRID K2 (K240Q GPU profile)

results with Haswell processors & NVIDIA GRID K2 (K240Q GPU profile)

Here are the results when we push for more scalability, bringing the maximum number of VDI guests to 20 and 24. We have added a 15 second staggered start to emulate synthetic human behavior.

Revit 2015 users per server

Based on our findings, NVIDIA GRID provides the following performance and scalability metrics for Autodesk Revit 2015; using the lab equipment shown below, using the RFO benchmark, and in working with Autodesk and their emphasis on usability. Of course, your usage will depend on your models but this is guidance to help guide your implementation.

Source

Download the NVIDIA GRID vGPU APPLICATION GUIDE FOR AUTODESK REVIT 2015 ON VMWARE HORIZON here

NVIDIA GRID – AppGuide (ArcGIS Pro)

Hi All.

I want to share this with you all, Luke Wignall and his team from NVIDIA have created some great AppGuides, that helps with understanding how many users can you put on a NVIDIA GRID system with a K2 in a VMware environment. These guides are made together with vendors such as ESRI. The guides focus on following apps ESRI ArcGIS Pro.

In this blogpost my goal is to highlight the great work NVIDIA have done creating the scalability app guides and these guides helps you if you want to virtualize ESRI Pro with NVIDIA GRID and VMware Horizon. The guides are great – cause they give an idea what you would require in a virtualized environment and these can be reused for other virtualized platforms such as Citrix and Microsoft – keep in mind that results might be different. If you would like to get more informations about how the setup is configured and which methodology i recommend you read the AppGuide, you can download it in under source in the end of this article.

The appguides gives a great idea to understand the impact of CPU and how the GPU are giving value.

About ESRI ArcGIS Pro

ESRI ArcGIS Pro 1.0 is a Geographic Information Systems (GIS) application for mapping, visualizing, editing, and analyzing spatial data. Esri recommends a GPU for best end user experience, but as ArcGIS Pro 1.0 also generates heavy CPU load, this also needs to be considered in architecting your vGPU solution. The size of your map data, the concurrency of your users, and the level of interaction with 3D data all need to be considered when defining your user groups.

Results NVIDIA Appguide for ESRI ArcGis Pro

The following are the full results of our testing. The baseline was the 45 second draw time sum – anything greater than that value represented a worsening UX while less would be a better UX. Looking for both performance and scalability, we tested looking for the greatest number of virtual desktops, and therefore the greatest scalability, while still within performance expectations and the threshold of 45 seconds. It’s important to note that your users, your data, and your hardware will impact these results and you may decide a different level of performance or scalability is required to meet your individual business needs. Tests were also run to look for potential NUMA issues that can negatively impact performance. This is where the physical GPU and its PCI-e channels are tied to one physical CPU, while the virtual desktop is running on the other physical CPU, so communication with the physical GPU has to move over the QPI between the two physical CPUs. This creates a bottleneck and can cause performance issues. However, in our testing, the application is sufficiently CPU bound that NUMA affinity made little difference. The results in the table below show the decrease in performance as we increased vCPU counts, and then the increase in scalability with synthetic human behavior (think time):

ArcGIS – users per server

Based on NVIDIA Performance Engineering Lab findings, NVIDIA GRID provides the following performance and scalability metrics for Esri ArcGIS 3D Pro 1.0. These metrics are based on tests with the lab equipment shown in the graphic below, using the Esri API based “heavy 3D” benchmark and in working with Esri to determine acceptable performance. Of course, your usage will depend on your models, but this is guidance to help guide your implementation.

Source

Download the NVIDIA GRID vGPU APPLICATION GUIDE FOR ESRI ARCGIS PRO 1.0 – 3D ON VMWARE HORIZON here

NVIDIA GRID 2.0 integrated in Microsoft Azure

At Microsoft Azurecon 2015, NVIDIA announced that Microsoft will offer NVIDIA GPU-enabled professional graphics applications and accelerated computing capabilities to customers worldwide through its cloud platform, Microsoft Azure.

Deploying the latest version of NVIDIA GRID^™ in its new N-Series virtual machine offering, Azure is the first cloud computing platform to provide GRID 2.0 virtualized graphics for enterprise customers.

For the first time, businesses will have the ability to deploy NVIDIA Quadro® grade professional graphics applications and accelerated computing on-premises, in the cloud through Azure, or via a hybrid of the two using both Windows and Linux virtual machines. Azure will also offer customers supercomputing-class performance, with the addition of the Tesla Accelerated Computing Platform’s flagship Tesla® K80 GPU accelerators, for the most computationally demanding data center and high performance computing (HPC) applications.

Unprecedented Virtualized Graphics Performance

With NVIDIA GRID enterprises can deliver graphics intensive applications from companies such as Autodesk, ESRI and Siemens from the cloud to their users. Announced last month, NVIDIA GRID 2.0 provides the NVIDIA Quadro GPU driver support, features and performance that graphics-intensive applications require, as well as other enhancements including double the application performance of the previous generation of GRID GPUs and Linux OS support.

Supercomputing in the Cloud

The Tesla Accelerated Computing Platform is designed from the ground up for power-efficient, high performance computing (HPC), computational science, supercomputing, data analytics and deep learning applications.

Powering some of the world’s highest performance supercomputers, the Tesla platform delivers dramatically higher performance and energy efficiency than a CPU-only approach and unprecedented application throughput in the data center.

By deploying the Tesla K80 GPU accelerator in its N-Series virtual machines, Azure dramatically expands access to supercomputing-class performance, enabling enterprises worldwide to accelerate their most demanding workloads, without requiring them to invest in, build and maintain dedicated computing resources.

Azure N-series, a new family of Azure Virtual Machines

Available in preview within the next few months, the N-series will feature the NVIDIA Tesla Accelerated Computing Platform as well as NVIDIA GRID 2.0 technology, providing the highest-end graphics support available in the cloud today.

Source

NVIDIA

Microsoft

NVIDIA GRID 2.0

NVIDIA have released the next generation of GRID 2.0. GRID 2.0 is based on the Maxwell architecture and the GRID 1.0 (K1/K2) was based on the Kepler architecture. I have been working with the GRID 1.0 technology since 2012 and it have matured alot in its 2 years of history. When the K1/K2 was released they was first working with GPU pass-through and then vGPU got introduced and you could virtualize the GPUs and increase density, which people wanted. Citrix was with their hypervisor the first company that supported NVIDIA GRID 1.0 and they was also the first company integrating vGPU into their Citrix Studio, so companies could easier provisioning machines with either MCS technology or PVS technology. VMware supported GRID 1.0 vGPU technology in 2015 in their hypervisor VMware vSphere 6.0 and fully integrated with their EUC stack VMware View, so companies can fully provisioning machines. The great thing about GRID 2.0 is that there is no need for a conversation when to choose either a K1 or a K2, if you required GPU compute or GPU framebuffer, M60 are being added to the tope end of the range and bringing 2x the performance, and if you have bladeserver’s, you can add the powerfull vGPU technology into the bladeserver’s with the M6.

Please notice that M6 will 0nly be supporting newer architecture of vendors not old platforms.

Maxwell architecture

Maxwell architecture is the new architecture of GPUs and a powerful GPU you might know is the Titan X

New GPUs GRID 2.0 and specifications

In GRID 2.0 NVIDIA now have a GPU for blade servers a MXM single socket, High-end GPU called M6

In GRID 2.0 NVIDIA replaces K1/K2 with the new PCIe 3.0 Dual Socket, Dual High-end GPU called M60
The M60 delivers 4096 CUDA or compute and 16GB GDDR5 memory/framebuffer

The M60 has 6x the h.264 encoders of the K2, and also Maxwell supports 4:4:4 chroma sub sampling, which is great news for encoders.

Certified GRID 2.0 servers

Click the link to see which servers are certified for M60 and M6
http://www.nvidia.com/object/grid-certified-servers.html

M6 have following servers supported:

M60 have following servers supported:

vGPU software editions and license

NVIDIA GRID 2.0 software is available in three editions that deliver accelerated virtual desktops to support the needs of your users. These editions include Virtual PC, Virtual Workstation, and Virtual Workstation Extended. GRID perpetual licenses are sold by Concurrent User (CCU).

NVIDIA GRID 2.0 (CCU) stands for ConCurrent User. So basically, per running VM as regardless of whether the user is connected to the VM or not, the VM is connected to the GPU and so consumes a license

NVIDIA GRID 2.0 software is much more than a “driver”. While the software package does include a guest driver for Windows and Linux, it also includes the NVIDIA GRID vGPU manager for VMware vSphere and Citrix XenServer, as well as the license server and M6/M60 mode switching utility.

NVIDIA Tesla M6 and M60 profiles are specific to the M6 and M60. There will be similar profiles as to what NVIDIA had on K1 and K2 (512 MB through 4 GB), all with twice the number of users on M6/ M60 compared to K1/K2. Plus, there is an additional 8 GB profile on M6/M60 which also adds support for CUDA, which wasn’t available on K1/K2.

NVIDIA GRID 2.0 is Maxwell only. If you are an existing customer K1/K2 are unchanged and will remain as a parallel option.

The NVIDIA GRID 2.0 solution

Summary

GA of NVIDIA GRID 2.0 (M60 and M6) will be 15 September 2015.

To get NVIDIA GRID 2.0 if you are a Citrix customer you need:
Server hardware that supports NVIDIA GRID 2.0 +NVIDIA GPU M60 or M6 + NVIDIA vGPU Software license + Citrix XenDesktop or XenApp License (XenServer is included in XD/XA licenses)

To get NVIDIA GRID 2.0 if you are a VMware customer you need:
Server hardware that supports NVIDIA GRID 2.0 +NVIDIA GPU M60 or M6 + NVIDIA vGPU Software license + VMware Horizon license (Horizon includes vSphere for Desktop)

If you are a Citrix customer that wants to run on VMware vSphere you need:

Server hardware that supports NVIDIA GRID 2.0 + NVIDIA GPU M60 or M6 + NVIDIA vGPU Software license + Citrix XenDesktop or XenApp License + VMware vSphere Enterprise Plus license or vSphere for Desktop license

Source

NVIDIA GRID Test Drive

NVIDIA GRID Website

NVIDIA GRID News

NVIDIA GRID YouTube Channel

Questions? Ask on our Forums

NVIDIA GRID on LinkedIn

Follow NVIDIAGRID on Twitter

Citrix License FAQ regarding vGPU

Vmware License FAQ regarding vGPU

Citrix HDX 3D Pro beyond limits part 1

Hi All

This is a video blog post series I am creating to show you as an audience how powerful remote graphics is from Citrix & NVIDIA.
You are now able to work from anywhere, any time, any device. You just need an internet connection (Satellit, Edge/3G)

This video shows the user experience with Citrix XenDesktop 7.6 VDI workload (virtualized Windows 8.1 64bit) The workload have a NVIDIA GRID K2 vGPU K220Q GPU profile assigned.

The workload is running in a datacenter in EMEA and secured by Citrix Netscaler and SMS Passcode.

The end device that is used to connect to the Citrix workload is a Microsoft Surface Pro 3 using Windows 10 and Citrix Receiver 14.3

Video is recorded by Apple iPhone 6+

Microsoft Surface Pro 3 is connected using my Phones internet connetion which was at that time switching between “EDGE” and “3G”. Bandwidth was 300KB-5Mbit and latency is from 500MS-7000MS, jitter is not meassured.

Please notice this video is recorded on a boat sailing between Denmark and Sweden in Europe, this trip took place July 2015.

Purpose of this video:

Show the audience how powerful Citrix HDX 3D Pro is using NVIDIA GRID in extreme conditions with latency I have never tried it on and I was still able to interact realtime with computer graphics thats running securely in a datacenter in EMEA.

This technology is so powerful and can be used in critical conditions where an employee can access graphics, (2D, 3D) or even rich graphics such as browsers, viewers, office productivity, erp systems. Imagine an engineer on an Oil rig requires to see a critical component that requires to be changed and the data can be accesable connected to a datacenter thousands of kilometers away securely and remotely. This is the future of working, making you work on any device, any where, any place.