NVIDIA vGPU - Introduction to NVIDIA Virtual GPU
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Lee Bushen, Senior Solutions Architect at NVIDIA covers the basics of NVIDIA Virtual GPU. - Why vGPU? - How does it work? - What are the main considerations for VDI? - Which GPU is right for me? - Which License do I need?
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NVIDIA vGPU - Introduction to NVIDIA Virtual GPU
- 1. Lee Bushen – Senior Solution Architect Professional Visualization – Virtualization INTRODUCTION TO VIRTUAL GPU
- 2. 2 3 FACTORS CONTRIBUTING TO VDI MARKET GROWTH Workplace Flexibility and Business Agility Security & Risk Management Reduced CAPEX and OPEX Source: BusinessWire. Global Virtual Desktop Infrastructure (VDI) Market to Grow Rapidly Through 2021, Due to Its Ability to Offer Improved Security and Flexibility to Enterprises: Technavio. http://www.businesswire.com/news/home/20161111005754/en/Global-Virtual-Desktop-Infrastructure-VDI-Market-Grow
- 3. 3 PERFORMANCE FROM THE DATA CENTER NVIDIA Virtual GPU technology delivers graphics accelerated virtual desktops and applications All devices have graphics Virtual machines also need a GPU
- 4. 4 Windows 7 Digital Worker on Windows 10 in 2017 Digital Worker on Windows 10 in 2018 Digital Worker on Windows 10 in 2019 ? 30% more graphics* 20% more graphics* 50% more graphics usage from Windows 7 to Windows 10 in 2018* GRAPHICS USAGE OF WINDOWS ENVIRONMENTS *Measured by the percent of time consuming GPU (DirectX or OpenGL). Windows 10 builds in 2017 include 1709, 1703 and 1607. Windows 10 builds in 2018 include 1803 and 1709 INCREASING DEMAND FOR GRAPHICS
- 5. 5 THE NEW DIGITAL WORKER They Way we Work is Changing Windows 10 Office 365/Office 2016 Web Browsers Collaboration and Video 50% increase in CPU requirement over Windows 71 Modern browsers are hardware accelerated by default Digital Imaging & Design Multi-, High Res Monitors 50-85% increase in CPU requirements over Windows 71 Latest Web Standards Flash, HTML5, and WebGL are all very taxing to the CPU Skype and YouTube are now prevalent across the enterprise Some features in Adobe® Photoshop® won’t work without a GPU2 Multi-monitors is the normal and 4K is mainstream PDF Viewers Adobe® Acrobat® and Microsoft Edge are hardware accelerated by default
- 6. 6 MODERN APPS IN THE DIGITAL WORKPLACE Demands More GPU *Percent of time consuming GPU comparing Windows 7 to Windows 10 (DirectX or OpenGL) Applications that require graphics has doubled since 2012 Over half of enterprise users access at least one graphics accelerated app 36% 59%53% 64% 85% 409%2017 2018 49% 75% 91%66% 98% 482%
- 7. 7 WHY VIRTUAL GPU? Experience like local 33% lower CPU usage
- 8. 8 NVIDIA PROFESSIONAL TECHNOLOGIES “Quadro & RTX” Brands Under-desk Workstation products Data Center Server products “Tesla” Brand Workstation Cards (active cooling) Mobile GPUs: HPC/DL Pure Compute/Basic graphics Desktop Virtualization Desktop Graphics Quadro vDWS vPC vApps Architectures: K=Kepler M=Maxwell P=Pascal V=Volta T=Turing “GRID” 2014 2019 V100 RTX 8000 RTX 6000 P40 T4 M10 P6 No SW License SW Licenses Hypervisor vGPU/Passthrough RTX8000 RTX5000 RTX4000RTX6000 GV100 GP100 P6000 P4000 P2000P5000 P1000 P620 P400 P5200 P3200 P2000P4200 P1000 P600 P400 Bare Metal/Passthrough Tesla Cards (mostly passive cooling) vCS
- 9. 9 HOW IT WORKS Virtualisation without a GPU Server CPU Only VDI Hypervisor Apps and VMs
- 10. 10 HOW IT WORKS NVIDIA virtual GPU products deliver a GPU Experience to every Virtual Desktop NVIDIA Virtual GPU Profiles With NVIDIA Virtual GPU NVIDIA Graphics Drivers Apps and VMs NVIDIA Tesla GPU Server NVIDIA virtualization software Hypervisor
- 11. 11 HOW IT WORKS GPU Pass-Through With NVIDIA Virtual GPU NVIDIA Graphics Drivers Apps and VMs NVIDIA Tesla GPU Server Hypervisor (no NVIDIA Driver required) GPU Pass Through
- 12. 12 VIRTUAL MACHINE HYPERVISOR Hardware GPU Broker Certified HW & Configuration? Which GPU? Which Profile? NVIDIA Driver Monitoring Tools? Network B/W Resolutions & Multi-monitor? Endpoint HW User Type? Which remoting Solution? Protocols Used? Applications? Density? Links License Server License?
- 13. 13 Knowledge Worker Creative & Technical Professional APPLICATIONS? Approx. 100 Professional Visualisation AppsGeneral Business Applications Which GPU you choose will depend on your applications
- 14. 14 WHICH GPU? Creative & Technical Professional Tesla T4 - RTX6000* (RTX8000 for large models) (P40 if RTX6000 not certified) (V100 high end ProViz/HPC) Knowledge Worker Tesla T4 or M10* (NVIDIA M10 for lowest cost) (Tesla P6 for blade form factor) Q3’19 Edition * Always ensure the same card is used for PoC and production
- 15. 15 KNOWLEDGE WORKERS - WHICH GPU? 1 x NVIDIA M10 or 2 x NVIDIA T4 ? 32 User Density Good Performance Most cost-effective Same Footprint 140W power consumption H.264, H.265, VP9 codecs H.264 codec >=1TB of memory in host Deep Learning and Ray Tracing Not the latest GPU Knowledge Workers Low-End ProViz 225W power consumption >5K Displays
- 16. 16 NVIDIA QUADRO vDWS GUIDANCE Small/simple CAD models, video, Entry PLM Medium size/complexity CAD models, Basic DCC, Medical Imaging, PLM Large/complex CAD models, Advanced DCC, Medical Imaging Large/complex CAD models, Seismic exploration, complex DCC effects, 3D Medical Imaging Recon Largest CAD models, CAE, Photorealistic rendering, Seismic exploration, GPGPU compute Deep learning, immersive visualization, and double precision GPGPU compute applications RTX: Realtime ray tracing, AI, NVLink RTX: Realtime ray tracing, AI, NVLink RTX: Realtime ray tracing, AI AutoCAD, Revit, Inventor Solidworks, Siemens NX, Creo, CATIA, ArcGIS Pro Adobe CC Photoshop, Illustrator Adobe CC Premiere Pro, After Effects, Autodesk Maya, 3ds Max, Mari, Nuke Schlumberger, Halliburton PACS/Diagnostics Ansys, Abaqus, Simulia SOLIDWORKS Visualize, CATIA Live Rendering, VRay RT Tesla P40 Tesla V100 Tesla T4
- 17. 17 QUADRO RTX VIRTUAL WORKSTATIONS Positioning and Recommendations Light Users Small to medium models, scenes or assemblies with simple parts NVIDIA T4 or P6 Quadro Virtual Data Center Workstation (Quadro vDWS) 16 GB Medium Users Large assemblies with simple parts or small assemblies with complex parts NVIDIA T4 or P6 Quadro vDWS 16 GB Type of User Recommended Solution GPU Memory Multiple Quadro P1000 Up to Quadro P4000 Equivalent Performance K2, M60, P4, M6Replaces K2, M60, P4, M6 Heavy Users Massive datasets, very large 3D models, complex designs, large assemblies NVIDIA Quadro RTX 8000, RTX 6000, P40 or V100 with Quadro vDWS Up to Quadro RTX 8000 N/A 48 GB/32 GB/24 GB *Recommendations are based on Perf/$
- 18. 18 NVIDIA DATA CENTER GPUs V100 P40 RTX 8000 RTX 6000 T4 M10 P6 GPUs / Board (Architecture) 1 (Volta) 1 (Pascal) 1 (Turing) 1 (Turing) 1 (Turing) 4 (Maxwell) 1 (Pascal) CUDA Cores 5,120 3,840 4,608 4,608 2,560 2,560 (640 per GPU) 2,048 Tensor Cores 640 --- 576 576 320 --- --- RT Cores --- --- 72 72 40 --- --- Memory Size 32 GB/16 GB HBM2 24 GB GDDR5 48 GB GDDR6 24 GB GDDR6 16 GB GDDR6 32 GB GDDR5 (8 GB per GPU) 16 GB GDDR5 vGPU Profiles 1 GB, 2 GB, 4 GB, 8 GB, 16 GB, 32 GB 1 GB, 2 GB, 3 GB, 4 GB, 6 GB, 8 GB, 12 GB, 24 GB 1 GB, 2 GB, 3 GB, 4 GB, 6 GB, 8 GB, 12 GB, 16 GB, 24 GB, 48 GB 1 GB, 2 GB, 3 GB, 4 GB, 6 GB, 8 GB, 12 GB, 24 GB 1 GB, 2 GB, 4 GB, 8 GB, 16 GB 0.5 GB, 1 GB, 2 GB, 4 GB, 8 GB 1 GB, 2 GB, 4 GB, 8 GB, 16 GB Form Factor PCIe 3.0 Dual Slot & SXM2 (rack servers) PCIe 3.0 Dual Slot (rack servers) PCIe 3.0 Dual Slot PCIe 3.0 Dual Slot PCIe 3.0 Single Slot (rack servers) PCIe 3.0 Dual Slot (rack servers) MXM (blade servers) Power 250W/300W 250W 295W 295W 70W 225W 90W Thermal passive passive active active passive passive bare board BLADE Optimized PERFORMANCE Optimized Recommended for Virtualization DENSITY Optimized
- 19. 19 “THE STACK!”
- 20. 20 EXPANDING THE NVIDIA VIRTUAL GPU PORTFOLIO Creative & Technical ProfessionalUse Case Virtual GPU Software Edition Recommended GPU (supported GPUs) Knowledge Worker GRID Virtual PC GRID Virtual Apps NVIDIA T4 or M10 (NVIDIA P6 for blade form factor) Client ComputingCompute Type Quadro Virtual Data Center Workstation NVIDIA T4 or Quadro RTX 6000, RTX 8000 (NVIDIA P40, P100, V100 P6 for blade form factor) Client Computing Creative & Technical Professional vComputeServer NVIDIA V100 or T4 (NVIDIA P40, P100, Quadro RTX 6000, RTX 8000, P6 for blade form factor) AI, Deep Learning, Data Science, & HPC Server Workloads Further details: https://images.nvidia.com/content/grid/pdf/Virtual-GPU-Packaging-and-Licensing-Guide.pdf
- 21. 21 vGPU LICENSE DECISION Do you use professional graphics apps for CAD, CAE, rendering, and other similar workloads? Do you use VDI for knowledge workers who require a native-like PC experience? You need Quadro vDWS Includes vCS, vPC, vApps entitlement Do you have multiple users sharing a single OS through sessions? (e.g., RDSH) You need GRID vPC Includes vApps entitlement Yes! Yes! No No You need GRID vAppsYes! Are you running AI/DL/HPC/Data Science workloads? No You need NVIDIA vComputeServer Yes! More questions? Ask your NVIDIA Partner!
- 22. 22 UNDERSTANDING PROFILES T4-1Q Architecture: • Kepler • Maxwell • Pascal • Volta • Turing Model Number Framebuffer Size: 0,1,2,4,8,16 Software License Reqd: • A - vApp • B – vPC “Business” • C - vComputeServer • Q – Quadro vDWS https://docs.nvidia.com/grid/latest/grid-vgpu-user-guide/index.html
- 23. 23 DESKTOP HOSTING MODELS Hosted Shared Virtual Desktops “XenApp” model Shared GPU (Either Pass-thru or large vGPU Profile) Frame Buffer Frame Buffer Frame Buffer Frame Buffer
- 24. 24 DESKTOP HOSTING MODELS Dedicated Virtual Desktops “XenDesktop” or “VDI” model Shared GPU (Split via vGPU Profile) Frame Buffer Frame Buffer Frame Buffer Frame Buffer Frame Buffer Frame Buffer
- 25. 25 Yes Use Video Codec for Compression Do Not Use Video Codec For Actively Changing Regions Or Use When Preferred & Do NOT optimize for 3D Graphics For the Entire Screen Or Use When Preferred & Optimize for 3D Graphics Visual Quality Always Lossless Visually Lossless & Client 4:4:4 Build to Lossless L/M/H Always Lossless Build to Lossless L/M/H Always Lossless B2L Or L/M/H Full-screen H264 4:4:4 Lossless RLE Full-screen H264 4:4:4 B2L Full-screen H264 4:2:0 Lossless RLE JPEG + RLE Lossless RLE JPEG + RLENo Yes No Yes No NoYes H264 + JPEG + RLE Yes No H264 4:2:0 + RLE B2L H264 4:2:0 + RLE B2L JPEG + RLE B2L JPEG + RLE B2L client S.H264 7.18+ & client S.H264 7.18+ & client S.H264 Visually Lossless & Client 4:4:4 XenDesktop Policy Evaluation and Codec Selection Visual Quality Visual Quality
- 26. 26 MUST READ LINKS Planning Main vGPU Documentation Is your HW Compatible? Is your software compatible? Which License? Get 90 day Evaluation Licenses vGPU Software Download (NVIDIA Licensing Portal) Windows 10 Sizing Guide Implementation Deployment Guides for Citrix/VMware License Server Install Docs GPU Profiler & Remote Display Analyser tools Bedtime Reading Rise of the Knowledge worker IDC Report Citrix Protocols and GPU Quantifying the Impact of GPU
Notes de l'éditeur
- As more organizations enable digital transformation and Windows 10 they are turning towards VDI. According to analysts, there are 3 factors Contributing to VDI adoption. The first is workplace flexibility and business agility. This means being untethered and being able to work from any device, anywhere. The second is improved security. With the rise in the global workforce coupled with more sophisticated threats, it becomes all the more important that intellectual property and mission-critical data are securely hosted within the data center, and not on end-user devices. And let's not forget these threats can be cyber attacks, but they can also be brought about by nature - hurricanes, earthquakes, etc. And third, VDI also results to lower CAPEX and OPEX from being able to have a cost effective infrastructure that scales out to more users with better manageability. http://www.businesswire.com/news/home/20161111005754/en/Global-Virtual-Desktop-Infrastructure-VDI-Market-Grow
- Application and desktop virtualization solutions have been around for a long time, but their number one point of failure tends to be user experience. The reason is very simple. When applications and desktops were first virtualized, GPUs were not a part of the mix. This meant that all of the capture, encode and rendering that was traditionally done on a GPU in a physical device, was being handled by the CPU in the host. While it was functional for some of the more basic applications it never truly met the native experience and performance levels that most users needed. Then a few years ago, NVIDIA released our virtual GPU solution which allowed you to virtualize a datacenter GPU and share it across multiple VMs. This not only improved performance for existing application and desktop environments, it also opened up a whole new set of use cases that could leverage this technology.
- Windows 10 was developed with hardware acceleration in mind. Hardware acceleration means using a computer’s hardware to do certain tasks and functions faster than is possible using software. Moving graphics rendering from the CPU to the GPU allows better graphics performance. Because Windows 10 is fully accelerated using a GPU by default, or is left to emulate a GPU with software rendering when one is unavailable, the operating system’s full potential can’t be realized without graphics acceleration. Furthermore, for most of the latest the applications, HW acceleration is turned on by default. Apps like Office 365, MS teams , PDF viewers and Web Browsers will generally use HW acceleration for all WebGL, videos, and zoom, pan, scroll operations. It has become tougher to disable Win10 features during the initial releases. For the later releases, while there are options to disable visual effects and animations to decrease resource utilization, you cannot completely turn off the Metro/Modern UI. Stripping down the system and removing apps and services would result to end user dissatisfaction as free Windows 10 upgrades for consumers drive expectations for the same quality of experience at work to be productive.
- Beyond Windows 10 and office productivity applications requiring more CPU consumption, nearly everything that the modern digital worker does today has become more CPU intensive. Modern browsers like Chrome and Internet Explorer all enable hardware acceleration by default. Often you need to go under advanced settings if you want to use software rendering. The latest standards like WebGL, currently used in 53% of the top 100 websites, can cause the CPU to hit 100% when just animating a simple scene. PDF viewers are likewise hardware accelerated by default. Video conferencing applications like Skype for Business and streaming sites like YouTube are becoming prevalent across the enterprise and are likewise very taxing to the CPU. Creative and design tools like Adobe Photoshop® have features that simply won’t work without a GPU and features that require GPU for acceleration. And lastly, we are seeing trends in use of multiple, high resolution monitors, which significanltly increase the number pixels required to encode and render, thereby increasing CPU utilization. All of these make GPUs even more relevant today, as GPUs help offload tasks from the CPU to ensure users get a great experience and can stay productive.
- The previous slides showed you how much more graphically intensive Windows 10 has become. It only makes sense that the apps that get upgraded as part of the Windows 10 upgrade also require more GPU resources. We worked our partner Lakeside Software and they have a product called SysTrack. One of the things SysTrack does is allow you to deploy an agent out to desktops that gather data and statistics about what applications are installed, how much memory is there, how much memory is being used – and they allow customers to opt in to share that data anonymously as part of a community program. We looked at Lakeside data for about 3M desktops over 5 years and found that the percentages of applications that require graphics acceleration has doubled in the past five years. The data shown here is comparing common office productivity applications used in Windows 7 to their counterparts used in Windows 10. As you can see, the Windows 10 versions drive a higher level of computer graphics than their counterparts in Windows 7. What is equally more striking is how just within a year from 2017 to 2018, you an see how much more GPU hungry these applications has become. – up to 482% higher for Skype, for example. Professional applications like SOLIDWORKS, CATIA, etc. require GPUs to support graphics acceleration, but what is clear from this data, is that even common business applications need GPU resources to run efficiently. And, of course this will continue to grow.
- Before I go into my presentation, I’d like to spend a minute or two talking about the technology and how different a virtual GPU enabled VDI environment is over a traditional CPU only environment. On the left we’re showing a traditional virtualization environment powered only by a CPU. The virtualization layer (or hypervisor), is installed on the server. The hypervisor abstracts the underlying hardware, making it accessible to multiple virtual desktops or guest VMs running on a virtualized host. When a user is working on a virtual desktop, all of the graphics commands from within the virtual desktop or application are intercepted by a generic driver within the guest OS, and are passed down via the hypervisor, to be captured and rendered on the CPU. This drives up CPU consumption and lowers density On the right, is an NVIDIA virtual GPU enabled VDI environment. Here, we have GPUs in the server, and the NVIDIA vGPU manager software that resides within the hypervisor. The NVIDIA software enables multiple VMs to share a single GPU, provisioning virtual GPUs for every VM. In addition to providing a better user experience, it also enables support for more users on a server because work that was typically done by the CPU, can be offloaded to the GPU.
- Before I go into my presentation, I’d like to spend a minute or two talking about the technology and how different a virtual GPU enabled VDI environment is over a traditional CPU only environment. On the left we’re showing a traditional virtualization environment powered only by a CPU. The virtualization layer (or hypervisor), is installed on the server. The hypervisor abstracts the underlying hardware, making it accessible to multiple virtual desktops or guest VMs running on a virtualized host. When a user is working on a virtual desktop, all of the graphics commands from within the virtual desktop or application are intercepted by a generic driver within the guest OS, and are passed down via the hypervisor, to be captured and rendered on the CPU. This drives up CPU consumption and lowers density On the right, is an NVIDIA virtual GPU enabled VDI environment. Here, we have GPUs in the server, and the NVIDIA vGPU manager software that resides within the hypervisor. The NVIDIA software enables multiple VMs to share a single GPU, provisioning virtual GPUs for every VM. In addition to providing a better user experience, it also enables support for more users on a server because work that was typically done by the CPU, can be offloaded to the GPU.
- Before I go into my presentation, I’d like to spend a minute or two talking about the technology and how different a virtual GPU enabled VDI environment is over a traditional CPU only environment. On the left we’re showing a traditional virtualization environment powered only by a CPU. The virtualization layer (or hypervisor), is installed on the server. The hypervisor abstracts the underlying hardware, making it accessible to multiple virtual desktops or guest VMs running on a virtualized host. When a user is working on a virtual desktop, all of the graphics commands from within the virtual desktop or application are intercepted by a generic driver within the guest OS, and are passed down via the hypervisor, to be captured and rendered on the CPU. This drives up CPU consumption and lowers density On the right, is an NVIDIA virtual GPU enabled VDI environment. Here, we have GPUs in the server, and the NVIDIA vGPU manager software that resides within the hypervisor. The NVIDIA software enables multiple VMs to share a single GPU, provisioning virtual GPUs for every VM. In addition to providing a better user experience, it also enables support for more users on a server because work that was typically done by the CPU, can be offloaded to the GPU.
- Click on each link to launch either the relevant web page or go to the relevant slide To return to this “holding” slide, press the Green BACK Arrows at the bottom of the following slides.
- With our portfolio of virtual GPU technology we enable accelerated productivity across a wide range of users and applications. For the knowledge worker, this would be office applications, browsers, high definition video, etc. For the creative and technical professional, NVIDIA virtual GPU technology enables virtual access to power user applications such as Dassault’s CATIA, Autodesk Revit, Petrel, and others – some of which you can see represented on the right side of this slide.
- Here is what our Tesla (and Quadro) cards look like in real life including the old K1/K2 cards. Taken in the UK NVIDIA lab. Notice that the P4 and T4 are very small single PCI slot cards compared to the others. Also note that the RTX 6000 was originally designed as a workstation card and so has a fan (active cooling) and has video ports out the back. Tesla cards don’t have video ports as they are designed to be used virtualised and connected to via a remoting protocol. Also note that power connections are subtly different from each other due to differing power needs. This is why it’s always best to source a server and card from an OEM. To ensure correct power and cables are used. Refer to each cards “Product Brief” to find exact power cable requirements. Product Briefs: https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/tesla-t4/t4-tensor-core-product-brief.pdf https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/tesla-product-literature/Tesla-P40-Product-Brief.pdf https://images.nvidia.com/content/tesla/pdf/Tesla-V100-PCIe-Product-Brief.pdf https://images.nvidia.com/content/pdf/tesla/Tesla-M10-Product-Brief.pdf https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/solutions/resources/documents1/Tesla-P6-Product-Brief.pdf
- With vComputeServer, the NVIDIA virtual GPU portfolio expands beyond client computing. vComputeServer virtualizes server workloads for AI, Deep Learning, Data Science, and HPC. The NVIDIA V100 and T4 GPUs are recommended for use with vComputeServer, but Quadro RTX 6000, and RTX 8000 GPUs as well as NVIDIA Pascal based GPUs are also supported. In the client computing space, NVIDIA continues to offer the best virtual GPU solution for knowledge workers with GRID vPC/vApps, and creative and technical professionals with Quadro Virtual Data Center Workstation (also known as QvDWS).
- To help understand which vGPU license is right for you, this decision tree guides you through determining what you will need in your virtual environment. If you use CUDA or professional workstation applications for users like creative and technical professionals, then QvDWS is the software license that is right for your use case. If you use a virtual desktop with productivity apps for users like knowledge workers, then GRID vPC is the right software license for you. If you have multiple users sharing a single OS through sessions, then GRID vApps is the license that would fit you. If you are running AI, deep learning, data science or HPC compute workloads, the vComputeServer best fits your workflow. If you are still unsure what is the best vGPU software solution for you, please contact your NVIDIA partner for assistance.