Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6

Total Page:16

File Type:pdf, Size:1020Kb

Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 VMware Horizon 6.2 TECHNICAL WHITE PAPER Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 Table of Contents Introduction . 4 Architectural Innovations . 4 Technological Foundation . .5 About This Paper . 5 Types of Graphics Acceleration . 6 Soft 3D . 6 vSGA . 6 vGPU . 7 vDGA. .. 7 Prerequisites . 8 Hardware Requirements . 8 Software Requirements. 9 Client Device Requirements . 9 Application Requirements . 10 DirectX 9.0c . 10 OpenGL 2.1 . 10 CUDA . 10 ESXi Installation and Configuration . 11 Confirm Graphics-Card Installation. 11 Install the GPU vSphere Installation Bundle (VIB) . 12 Start the Xorg Service . 13 Uninstall and Update the GPU VIB . 14 Post-Installation Checks. 14 Xorg . 14 gpuvm . 14 nvidia-smi .. 15 Log Files . 15 Enabling GPU Pass-Through for vDGA and vGPU . 16 Enable the Host for GPU Pass-Through . 16 Verify That VT-d or AMD IOMMU Is Enabled . 16 Enable Device Pass-Through Using the vSphere Web Client . 16 Virtual Machine Configuration and Setup . 17 Configure Virtual Machine Video Card 3D Capabilities . 17 Enable the Virtual Machine for vDGA or vGPU . 18 TECHNICAL WHITE PAPER / 2 Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 View Setup and Configuration . 20 Pool Prerequisites for View in Horizon 6 . 20 Enabling View Pools for Hardware 3D Rendering . 20 Enable an Existing View Pool . 20 Enabling a New View Pool. 20 Video-Memory (VRAM) Sizing . 21 Screen Resolution . 21 Pool 3D-Rendering Options in View . 22 Manage Using vSphere Client . 23 Automatic . 23 Software . 23 Hardware . 23 Disabled. 23 NVIDIA GRID vGPU . 23 Best Practices for Configuring 3D Rendering in Horizon 6 . 24 When to Select the Automatic Option . 24 When to Select the Hardware Option . 24 When to Select the Manage Using vSphere Client Option . 24 When to Select the Software Option . 24 Performance Tuning Tips and Best Practices . 25 Virtual Machine Configuration . 26 Virtual Machines Using VMXNET3 . 26 Configuring Adequate Virtual Machine Resources, vCPU, and vRAM . 26 Optimizing PCoIP . 26 Enabling Relative Mouse . 27 Workaround for CAD Performance Issues . 27 Resource Monitoring . 27 gpuvm . 27 nvidia-smi . 28 Troubleshooting . 29 About the Authors and Contributors . 31 References . 31 TECHNICAL WHITE PAPER / 3 Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 Introduction Engineers, designers, and scientists have traditionally relied on dedicated graphics workstations to perform the most demanding tasks, such as manipulating 3D models and visually analyzing large data sets. These standalone workstations carried high acquisition and maintenance costs, and they required the user to be present in the lab or office. In areas such as oil and gas, space exploration, aerospace, engineering, science, and manufacturing this meant that an organization’s individuals had to be located in the same physical location as the workstation. Virtualizing the graphics workstation provides immediate benefits by enabling workers to collaborate and be productive from any location, using any endpoint device. This enables organizations to employ the best global talent available and work more easily with valued partners and suppliers. Virtualization also offers both CapEx and OpEx savings, driving down acquisition and maintenance costs. Innovations in hardware-based graphics acceleration and virtualization technology have made graphics workstation virtualization a reality. With the latest generation of virtualization software, display protocols, and advanced graphics cards, virtual desktops can meet and even exceed the performance expectations of designers and researchers accustomed to working on high-end standalone graphics workstations. The ability of a single physical GPU to support multiple users also has important implications for IT as well as for users who are increasingly accustomed to mobility. Architectural Innovations Moving the graphics acceleration hardware from the workstation to a server is a key architectural innovation. This shift changes the computing metaphor for graphics processing, putting the additional compute, memory, networking, and security advantages of the data center at the disposal of the user, so that complex models and very large data sets can be accessed and manipulated from virtually anywhere. With appropriate network bandwidth and suitable remote client devices, IT can now offer the most advanced users an immersive 3D graphics experience while freeing them from the limitations of the old computing metaphor. Fewer physical resources are needed, the wait time to open complex models or run simulations is greatly reduced, and users are no longer tied to a single physical location. With vGPU, several advanced graphics users can typically be hosted on a single physical GPU without diminishing performance. A vSGA solution enables a larger number of users who run less intensive workloads or who require only occasional access to the shared GPU. With vDGA, a GPU is reserved for the exclusive use of a single user. A vDGA solution can be used to meet specific compatibility requirements, but it provides a low consolidation benefit. Centralizing graphics workloads in the data center also simplifies the management, provisioning, and maintenance of desktops, applications, and data. TECHNICAL WHITE PAPER / 4 Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 Technological Foundation The key enabling technologies for these solutions are: • Graphics cards that support GPU virtualization - NVIDIA GRID - NVIDIA Tesla - AMD FirePro - Intel HD Graphics P4700 • VMware vSphere® 5.1 or later • VMware View® 5.3 or later (now called View in VMware Horizon® 6) • Protocols - PCoIP - Secure WebSocket protocol for remote display • VMware vRealize® Operations Manager™ About This Paper This paper begins by explaining the differences between the four types of graphics acceleration, matching them with typical use cases. Later sections provide installation and configuration instructions as well as best practices and troubleshooting. For a more detailed discussion of use cases, sizing, and test results, see the VMware Horizon 6 3D Engineering Workloads Reference Architecture. TECHNICAL WHITE PAPER / 5 Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 Types of Graphics Acceleration Horizon 6 offers four types of 3D graphics acceleration, which map fairly closely to four common use cases. Oil and Gas Architecture Design Diagnostics Image Engineering Quality Lightweight CAD Interactivity Media and Graphics 3D Viewers Cost per Seat GIS WebGL Productivity Apps with Graphics Aero vDGA vSGA Soft 3D NVIDIA GRID vGPU Light Users Heavy Users Fewer Applications Many Applications Task Worker Knowledge Worker Power User Designer Figure 1: 3D Technologies for Different Use Cases Soft 3D Software-based Soft 3D is included in all editions of Horizon 6 to provide improved performance for users who can be characterized as task workers. Those who perform routine office tasks, or who spend most of their time coding, or even writing about graphics, can benefit from this technology without requiring a hardware-based solution. vSGA Virtual Shared Graphics Acceleration (vSGA) provides a significant level of enhancement for office workers and executives—people who create or manipulate 2D or 3D graphics using Microsoft Office, Adobe Photoshop, and other non-specialized end-user applications. A vSGA solution can improve performance for this use case and provide high levels of consolidation of users across GPUs. One graphics acceleration card installed on the vSphere host can support a large number of users who require only occasional access, and many physical servers can support multiple graphics acceleration cards. Virtual Shared Graphics Acceleration does not support all graphics API versions and may not be supported by certain ISVs. The vSGA solution uses a proprietary VMware graphics driver that provides an abstraction layer on top of the physical GPU, so that virtual desktops benefit from hardware acceleration, but they do not have direct physical access to the GPU. This arrangement allows functionality such as VMware vSphere vMotion® but means that not all graphics APIs are supported. TECHNICAL WHITE PAPER / 6 Deploying Hardware-Accelerated Graphics with View Virtual Desktops in Horizon 6 vGPU Virtual Graphics Processing Unit (vGPU) is similar in concept and design to vSGA, but it provides mediated, direct access to the physical GPU—so multiple users can share a single GPU—using native graphics card drivers. NVIDIA GRID cards can support several engineers, data scientists, and designers who rely on advanced graphics software such as CAx applications, with performance that can meet or exceed that of a traditional dedicated workstation. This is usually the most cost-effective solution both for large enterprises and for small-to-medium- sized design studios, largely because of the cost savings that result from supporting several designers per graphics card instead of one. A vGPU solution supports OpenGL and DirectX graphic APIs. With NVIDIA GRID 2.0, vGPU can also support OpenCL and NVIDIA CUDA. GRAPHICS PHYSICAL VIRTUAL USE FRAME MAXIMUM MAXIMUM vGPUs CARD GPUs GPU CASE BUFFER NUMBER OF DISPLAYS PER USER AT MAXIMUM RESOLUTION PER PER OF GPU GRID 2560x1600 CARD K280Q Designer 4 GB 4 1 2 K260Q Designer 2 GB 4 2 4 GRID K2 2 K240Q Designer or 1 GB 2 4 8 Power
Recommended publications
  • GPU Virtualization on Vmware's Hosted I/O Architecture
    GPU Virtualization on VMware’s Hosted I/O Architecture Micah Dowty, Jeremy Sugerman VMware, Inc. 3401 Hillview Ave, Palo Alto, CA 94304 [email protected], [email protected] Abstract more computational performance than CPUs. At the Modern graphics co-processors (GPUs) can produce same time, GPU acceleration has extended beyond en- high fidelity images several orders of magnitude faster tertainment (e.g., games and video) into the basic win- than general purpose CPUs, and this performance expec- dowing systems of recent operating systems and is start- tation is rapidly becoming ubiquitous in personal com- ing to be applied to non-graphical high-performance ap- puters. Despite this, GPU virtualization is a nascent field plications including protein folding, financial modeling, of research. This paper introduces a taxonomy of strate- and medical image processing. The rise in applications gies for GPU virtualization and describes in detail the that exploit, or even assume, GPU acceleration makes specific GPU virtualization architecture developed for it increasingly important to expose the physical graph- VMware’s hosted products (VMware Workstation and ics hardware in virtualized environments. Additionally, VMware Fusion). virtual desktop infrastructure (VDI) initiatives have led We analyze the performance of our GPU virtualiza- many enterprises to try to simplify their desktop man- tion with a combination of applications and microbench- agement by delivering VMs to their users. Graphics vir- marks. We also compare against software rendering, the tualization is extremely important to a user whose pri- GPU virtualization in Parallels Desktop 3.0, and the na- mary desktop runs inside a VM. tive GPU. We find that taking advantage of hardware GPUs pose a unique challenge in the field of virtu- acceleration significantly closes the gap between pure alization.
    [Show full text]
  • Caverns Measureless to Man: Interdisciplinary Planetary Science & Technology Analog Research Underwater Laser Scanner Survey (Quintana Roo, Mexico)
    Caverns Measureless to Man: Interdisciplinary Planetary Science & Technology Analog Research Underwater Laser Scanner Survey (Quintana Roo, Mexico) by Stephen Alexander Daire A Thesis Presented to the Faculty of the USC Graduate School University of Southern California In Partial Fulfillment of the Requirements for the Degree Master of Science (Geographic Information Science and Technology) May 2019 Copyright © 2019 by Stephen Daire “History is just a 25,000-year dash from the trees to the starship; and while it’s going on its wild and woolly but it’s only like that, and then you’re in the starship.” – Terence McKenna. Table of Contents List of Figures ................................................................................................................................ iv List of Tables ................................................................................................................................. xi Acknowledgements ....................................................................................................................... xii List of Abbreviations ................................................................................................................... xiii Abstract ........................................................................................................................................ xvi Chapter 1 Planetary Sciences, Cave Survey, & Human Evolution................................................. 1 1.1. Topic & Area of Interest: Exploration & Survey ....................................................................12
    [Show full text]
  • Gscale: Scaling up GPU Virtualization with Dynamic Sharing of Graphics
    gScale: Scaling up GPU Virtualization with Dynamic Sharing of Graphics Memory Space Mochi Xue, Shanghai Jiao Tong University and Intel Corporation; Kun Tian, Intel Corporation; Yaozu Dong, Shanghai Jiao Tong University and Intel Corporation; Jiacheng Ma, Jiajun Wang, and Zhengwei Qi, Shanghai Jiao Tong University; Bingsheng He, National University of Singapore; Haibing Guan, Shanghai Jiao Tong University https://www.usenix.org/conference/atc16/technical-sessions/presentation/xue This paper is included in the Proceedings of the 2016 USENIX Annual Technical Conference (USENIX ATC ’16). June 22–24, 2016 • Denver, CO, USA 978-1-931971-30-0 Open access to the Proceedings of the 2016 USENIX Annual Technical Conference (USENIX ATC ’16) is sponsored by USENIX. gScale: Scaling up GPU Virtualization with Dynamic Sharing of Graphics Memory Space Mochi Xue1,2, Kun Tian2, Yaozu Dong1,2, Jiacheng Ma1, Jiajun Wang1, Zhengwei Qi1, Bingsheng He3, Haibing Guan1 {xuemochi, mjc0608, jiajunwang, qizhenwei, hbguan}@sjtu.edu.cn {kevin.tian, eddie.dong}@intel.com [email protected] 1Shanghai Jiao Tong University, 2Intel Corporation, 3National University of Singapore Abstract As one of the key enabling technologies of GPU cloud, GPU virtualization is intended to provide flexible and With increasing GPU-intensive workloads deployed on scalable GPU resources for multiple instances with high cloud, the cloud service providers are seeking for practi- performance. To achieve such a challenging goal, sev- cal and efficient GPU virtualization solutions. However, eral GPU virtualization solutions were introduced, i.e., the cutting-edge GPU virtualization techniques such as GPUvm [28] and gVirt [30]. gVirt, also known as GVT- gVirt still suffer from the restriction of scalability, which g, is a full virtualization solution with mediated pass- constrains the number of guest virtual GPU instances.
    [Show full text]
  • Crane: Fast and Migratable GPU Passthrough for Opencl Applications
    Crane: Fast and Migratable GPU Passthrough for OpenCL Applications James Gleeson, Daniel Kats, Charlie Mei, Eyal de Lara University of Toronto Toronto, Canada {jgleeson,dbkats,cmei,delara}@cs.toronto.edu ABSTRACT (IaaS) providers now have virtualization offerings with ded- General purpose GPU (GPGPU) computing in virtualized icated GPUs that customers can leverage in their guest vir- environments leverages PCI passthrough to achieve GPU tual machines (VMs). For example, Amazon Web Services performance comparable to bare-metal execution. However, allows VMs to take advantage of NVIDIA’s high-end GPUs GPU passthrough prevents service administrators from per- in EC2 [6]. Microsoft and Google recently introduced simi- forming virtual machine migration between physical hosts. lar offerings on Azure and GCP platforms respectively [34, Crane is a new technique for virtualizing OpenCL-based 21]. GPGPU computing that achieves within 5:25% of pass- Virtualized GPGPU computing leverages modern through GPU performance while supporting VM migra- IOMMU features to give the VM direct use of the GPU tion. Crane interposes a virtualization-aware OpenCL li- through DMA and interrupt remapping – a technique which brary that makes it possible to reclaim and subsequently is usually called PCI passthrough [17, 50]. By running reassign physical GPUs to a VM without terminating the the GPU driver in the context of the guest operating guest or its applications. Crane also enables continued GPU system, PCI passthrough bypasses the hypervisor and operation while the VM is undergoing live migration by achieves performance that is comparable to bare-metal OS transparently switching between GPU passthrough opera- execution [47]. tion and API remoting.
    [Show full text]
  • A Full GPU Virtualization Solution with Mediated Pass-Through
    A Full GPU Virtualization Solution with Mediated Pass-Through Kun Tian, Yaozu Dong, David Cowperthwaite Intel Corporation Abstract shows the spectrum of GPU virtualization solutions Graphics Processing Unit (GPU) virtualization is an (with hardware acceleration increasing from left to enabling technology in emerging virtualization right). Device emulation [7] has great complexity and scenarios. Unfortunately, existing GPU virtualization extremely low performance, so it does not meet today’s approaches are still suboptimal in performance and full needs. API forwarding [3][9][22][31] employs a feature support. frontend driver, to forward the high level API calls inside a VM, to the host for acceleration. However, API This paper introduces gVirt, a product level GPU forwarding faces the challenge of supporting full virtualization implementation with: 1) full GPU features, due to the complexity of intrusive virtualization running native graphics driver in guest, modification in the guest graphics software stack, and and 2) mediated pass-through that achieves both good incompatibility between the guest and host graphics performance and scalability, and also secure isolation software stacks. Direct pass-through [5][37] dedicates among guests. gVirt presents a virtual full-fledged GPU the GPU to a single VM, providing full features and the to each VM. VMs can directly access best performance, but at the cost of device sharing performance-critical resources, without intervention capability among VMs. Mediated pass-through [19], from the hypervisor in most cases, while privileged passes through performance-critical resources, while operations from guest are trap-and-emulated at minimal mediating privileged operations on the device, with cost. Experiments demonstrate that gVirt can achieve good performance, full features, and sharing capability.
    [Show full text]
  • GPU Virtualization on Vmware's Hosted I/O Architecture
    GPU Virtualization on VMware's Hosted I/O Architecture Micah Dowty Jeremy Sugerman VMware, Inc. VMware, Inc. 3401 Hillview Ave, Palo Alto, CA 94304 3401 Hillview Ave, Palo Alto, CA 94304 [email protected] [email protected] ABSTRACT 1. INTRODUCTION Modern graphics co-processors (GPUs) can produce high fi- Over the past decade, virtual machines (VMs) have be- delity images several orders of magnitude faster than general come increasingly popular as a technology for multiplexing purpose CPUs, and this performance expectation is rapidly both desktop and server commodity x86 computers. Over becoming ubiquitous in personal computers. Despite this, that time, several critical challenges in CPU virtualization GPU virtualization is a nascent field of research. This paper have been overcome, and there are now both software and introduces a taxonomy of strategies for GPU virtualization hardware techniques for virtualizing CPUs with very low and describes in detail the specific GPU virtualization archi- overheads [2]. I/O virtualization, however, is still very tecture developed for VMware’s hosted products (VMware much an open problem and a wide variety of strategies are Workstation and VMware Fusion). used. Graphics co-processors (GPUs) in particular present a challenging mixture of broad complexity, high performance, We analyze the performance of our GPU virtualization with rapid change, and limited documentation. a combination of applications and microbenchmarks. We also compare against software rendering, the GPU virtual- Modern high-end GPUs have more transistors, draw more ization in Parallels Desktop 3.0, and the native GPU. We power, and offer at least an order of magnitude more com- find that taking advantage of hardware acceleration signif- putational performance than CPUs.
    [Show full text]
  • Feasibility of Using a Low‑Cost Head‑Mounted Augmented Reality Device in the Operating Room Pieter L
    Editor: OPEN ACCESS Pieter L. Kubben, MD, PhD Maastricht University Medical SNI: Computational For entire Editorial Board visit : Center, Maastricht, http://www.surgicalneurologyint.com The Netherlands Technical Note Feasibility of using a low‑cost head‑mounted augmented reality device in the operating room Pieter L. Kubben1,2, Remir S. N. Sinlae3 1Departments of Neurosurgery, 2Medical Information Technology, Maastricht University Medical Center, Maastricht, 3Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands E‑mail: *Pieter L. Kubben ‑ [email protected]; Remir S. N. Sinlae ‑ [email protected] *Corresponding author Received: 07 July 18 Accepted: 13 December 18 Published: 28 February 19 Abstract Background: Augmented reality (AR) has great potential for improving image‑guided neurosurgical procedures, but until recently, hardware was mostly custom‑made and difficult to distribute. Currently, commercially available low‑cost AR devices offer great potential for neurosurgery, but reports on technical feasibility are lacking. The goal of this pilot study is to evaluate the feasibility of using a low‑cost commercially available head‑mounted holographic AR device (the Microsoft Hololens) in the operating room. The Hololens is operated by performing specific hand gestures, which are recognized by the built‑in camera of the device. This would allow the neurosurgeon to control the device “touch free” even while wearing a sterile surgical outfit. Methods: The Hololens was tested in an operating room under two lighting conditions (general background theatre lighting only; and general background theatre lighting and operating lights) and wearing different surgical gloves (both bright and dark). All required hand gestures were performed, and voice recognition was evaluated against background noise consisting of two nurses talking at conversational speech level.
    [Show full text]
  • Enabling VDI for Engineers and Designers Positioning Information
    Enabling VDI for Engineers and Designers Positioning Information The ability to work remotely has been a critical business need for many years. But with the recent pandemic, the focus has shifted from supporting the occasional business trip or conference attendee, to supporting all non-essential employees. Virtual Desktop Infrastructure (VDI) provides a robust solution for businesses, allowing their employees to access business data on any mobile device – be it a laptop, tablet, or smartphone – without risk of losing that business data if the device is lost or stolen. With VDI the data resides in the data center, behind company firewalls. VDI allows companies to implement flexible work schedules, where employees have the freedom to pick up the kids from school and log on later in the evening to finish up. VDI also provides for centralized management of security fixes and application upgrades, ensuring all workers are using the latest version of applications. Although a great solution for your typical office workers, the benefits of VDI have largely been unavailable to another set of employees. Power users – engineers and designers using 3D or other graphics visualization applications – have generally been left out of these flexible arrangements. The graphics visualization applications they use are processor intensive, and the files they create and modify can be very large. The workstations that run the applications and the high-resolution monitors that display the designs are heavy and thus difficult to move. In order to have decent response times, power users have needed to be connected to a high-speed local area network. Work has been underway for several years to expand the benefits of VDI to the power user, and today solutions exist to support the majority of visualization applications.
    [Show full text]
  • 3D Models Specifications for Terraexplorer®
    3D Models Specifications for TerraExplorer® www.SkylineGlobe.co m All specifications are subject to change without notice -1- Table of Contents CHAPTER 1. SUPPORTED FORMATS ............................................................................... 3 CHAPTER 2. DIRECTX CONVERTERS .............................................................................. 7 CHAPTER 3. OPENFLIGHT CONVERTERS ........................................................................ 8 CHAPTER 4. MODEL BUILDING GUIDELINES ................................................................. 9 CHAPTER 5. EXPORT SETTINGS ................................................................................... 13 CHAPTER 6. STREAMING 3D MODELS USING POINT FEATURE LAYER .......................... 20 CHAPTER 7. SUMMARY ................................................................................................ 21 Last update: June 2009 The purpose of this document is to describe the 3D model formats that are available for use in TerraExplorer ® suite. It discusses the available functionality, conversion methods from different formats, and recommendations for efficient model creation for real-time rendering. All specifications are subject to change without notice -2- CHAPTER 1. SUPPORTED FORMATS TerraExplorer supports the import of the following 3D model file formats: . DirectX (*.X) . OpenFlight (*.FLT) . Google SketchUp 6 (*.KML, *.KMZ, *.DAE) Skyline internal formats: . Compressed DirectX (*.XPC) . Compressed DirectX with Level Of Details (*.XPL) . Compressed
    [Show full text]
  • Virtual GPU Software User Guide Is Organized As Follows: ‣ This Chapter Introduces the Capabilities and Features of NVIDIA Vgpu Software
    Virtual GPU Software User Guide DU-06920-001 _v13.0 Revision 02 | August 2021 Table of Contents Chapter 1. Introduction to NVIDIA vGPU Software..............................................................1 1.1. How NVIDIA vGPU Software Is Used....................................................................................... 1 1.1.2. GPU Pass-Through.............................................................................................................1 1.1.3. Bare-Metal Deployment.....................................................................................................1 1.2. Primary Display Adapter Requirements for NVIDIA vGPU Software Deployments................2 1.3. NVIDIA vGPU Software Features............................................................................................. 3 1.3.1. GPU Instance Support on NVIDIA vGPU Software............................................................3 1.3.2. API Support on NVIDIA vGPU............................................................................................ 5 1.3.3. NVIDIA CUDA Toolkit and OpenCL Support on NVIDIA vGPU Software...........................5 1.3.4. Additional vWS Features....................................................................................................8 1.3.5. NVIDIA GPU Cloud (NGC) Containers Support on NVIDIA vGPU Software...................... 9 1.3.6. NVIDIA GPU Operator Support.......................................................................................... 9 1.4. How this Guide Is Organized..................................................................................................10
    [Show full text]
  • With NVIDIA Virtual GPU
    Virtualizing AI/DL platform: NVIDIA Virtual GPU Solution Doyoung Kim, Sr. Solution Architect NVIDIA Virtual GPU Solution Support, Updates & Maintenance NVIDIA Virtual GPU Software Tesla Datacenter GPUs How it works? CPU Only VDI With NVIDIA Virtual GPU Apps and VMs NVIDIA Graphics Drivers Apps and VMs NVIDIA Virtual GPU Hypervisor NVIDIA virtualization software Hypervisor Server NVIDIA Tesla GPU Server Evolution of Virtual GPU Live Migration Ultra High End Simulation, NGC Support Photo Realism, 3D Rendering, AL/DL Business Designers, User Architects, Engineers 2013 2016 2017 Today GPU Compute on Virtual GPU Optimized DL Container from NGC Virtual Machine Virtual Quadro GPU CUDA & OpenCL enabled NVIDIA Virtualization Software Hypervisor NVIDIA Tesla GPU Server Virtual GPU can…. ✓ Run GPU compute workload - Any CUDA / OpenCL applications - Requires NVIDIA Virtual GPU 5.0 or higher - Requires Pascal or later GPU ✓ Be fully integrated with Virtualization solution - Live migration support from Virtual GPU 6.0 or higher - Support Cluster / Host / VM / Application level performance monitoring - Enabled for all major solutions such as vSphere / XenServer / KVM ✓ Provide every level of AI / DL Platforms - From desktop level to multi-GPU server - Fully support NVIDIA GPU Cloud (NGC) - Support up to 4 multi-vGPU per Virtual Machine* * Requires Virtual GPU 7.0 or higher / RHEL KVM only Why Virtualization? Which is best for AI/DL research system? PC with Consumer GPU GPU Server w/o Virtualization NVIDIA GPU Virtualization Manageability Require MGMT
    [Show full text]
  • GPGPU Task Scheduling Technique for Reducing the Performance Deviation of Multiple GPGPU Tasks in RPC-Based GPU Virtualization Environments
    S S symmetry Article GPGPU Task Scheduling Technique for Reducing the Performance Deviation of Multiple GPGPU Tasks in RPC-Based GPU Virtualization Environments Jihun Kang and Heonchang Yu * Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea; [email protected] * Correspondence: [email protected] Abstract: In remote procedure call (RPC)-based graphic processing unit (GPU) virtualization envi- ronments, GPU tasks requested by multiple-user virtual machines (VMs) are delivered to the VM owning the GPU and are processed in a multi-process form. However, because the thread executing the computing on general GPUs cannot arbitrarily stop the task or trigger context switching, GPU monopoly may be prolonged owing to a long-running general-purpose computing on graphics processing unit (GPGPU) task. Furthermore, when scheduling tasks on the GPU, the time for which each user VM uses the GPU is not considered. Thus, in cloud environments that must provide fair use of computing resources, equal use of GPUs between each user VM cannot be guaranteed. We propose a GPGPU task scheduling scheme based on thread division processing that supports GPU use evenly by multiple VMs that process GPGPU tasks in an RPC-based GPU virtualization environment. Our method divides the threads of the GPGPU task into several groups and controls the execution time of each thread group to prevent a specific GPGPU task from a long time monopolizing the GPU. The Citation: Kang, J.; Yu, H. GPGPU Task Scheduling Technique for efficiency of the proposed technique is verified through an experiment in an environment where Reducing the Performance Deviation multiple VMs simultaneously perform GPGPU tasks.
    [Show full text]