APRIL SILICON VALLEY, US S Monitoring Solutions for NVIDIA GRID

Transcription

1 APRIL SILICON VALLEY, US S Monitoring Solutions for NVIDIA GRID

2 Awarded Thomas Poppelgaard Independent Technology Evangelist Subject Matter Expert: Remote Graphics,Virtual Reality, Augmented _poppelgaard thomas@poppelgaard.com

3 Disclaimer Nothing of this data is sponsored by any of the mentioned vendors This analysis is to help you understand what each vendor can do with a GPU in physically and virtually world as of April 2016 All data is gathered from the 5 vendors and validated April 2016

4 Technologies I work with Remote Graphics Virtual Reality Augmented Reality 4

5 CPU Memory IOPS GPU compute GPU dedicate GPU shared CPU Memory IOPS GPU compute GPU dedicate GPU shared

6 Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is HP Confidential. Do not distribute.

7 Recommended whitepaper about Remote Graphics

8 Highlevel Remote graphics

9 Highlevel Remote graphics User Layer Access Layer Resource Layer Windows applications Windows desktops Linux desktops End point (pc, thin client, mobile) Protocol Gateway Physical PCs

10 Understanding Frame pr second Possibilities of monitoring frames pr second

11 Hardware FPS behaviour In a physical Workstation 56 FPS 46 FPS Machine FPS Application Specific FPS CPU Memory Storage Network GPU GPU Physically computer

12 Hardware FPS behaviour in a Remote Graphics solution Protocol FPS 46 FPS Machine FPS 56 FPS Protocol (RDP, PCOIP, Blast, HDX, Framehawk) 26 FPS Application specific FPS CPU Memory Storage Network GPU GPU Physically computer or virtual computer

13 Use case and user profiling Always use tools for assesments for apps to understand the pattern of usage of a GPU Understand telemetric data of an app using CPU/GPU and you have the success for profiling your user to a GPU

14 Assess Manage Architect Transform Pilot

15 Assess & Design STRATUSPHERE FIT VDI Compatibility What Do You Have? The desktop transformation process begins with a clear understanding of your current users, applications, operating systems and resource consumption details Application Inventory What Do You Have? What Do You Use? What Do You Need?

16 NVIDIA Assessment report Step 1 Identify Candidates for Grid card based on existing GPU card and application usage (known graphic intensive applications) Step 2 Match possible Grid profile (K120, K140, etc ) based on existing configuration (cores, Memory & displays)

17 NVIDIA Assessment report Step 3 Adjust recommended profile based on usage (peaks)

18 NVIDIA Assessment report Step 4 Compile for final report:

19 30days data collected maximum GPU usage

20 30days data collected maximum GPU usage

21 30days data collected maximum GPU usage

22 Machine GPU Usage 3% DirectX + OpenGL apps, 5 12% OpenGL Apps, 24 DirectX Apps, 70 85% High Medium Low DirectX Apps OpenGL Apps DirectX + OpenGL apps

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25 Machine UX metrics GPU identify GPU compute usage GPU memory usage GPU identify GPU compute usage GPU memory usage GPU identify GPU compute usaeg GPU memory usage

26 Application UX metrics GPU identify GPU compute usage GPU memory usage GPU identify GPU compute usage GPU memory usage GPU identify GPU compute usaeg GPU memory usage

27 FPS UX metrics FPS machine FPS apps FPS user (Citrix) protocol FPS user (Microsoft) protocol FPS user (Vmware) protocol

28 Protocol UX metrics Citrix protocol H264 Citrix protocol Thinwire+ Citrix protocol Framehawk Microsoft protocol RDP Vmware protocol PCOIP Vmware protocol Blast Extreme

29 Customized Dashboards (example GPU) Customize dashboards with GPU, CPU, Memory, IOPS values

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31 Ressources

32 Thank you Thomas _poppelgaard thomas@poppelgaard.com Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.