Best of NVIDIA GTC 2015

NVIDIA GTC 2015

Hi All

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After a succesfull NVIDIA GTC (gpu technology conference) in San Jose, March 2015. It was amazing all the brain gathered in one place, at NVIDIA GTC 2015, I had so many great conversations with friends, partners and there was one sentence I thought through “try to imagine what could you do for the world if we tried to build 1 thing with all this brain power in joined forces” . NVIDIA is doing amazing things and this year it was all about “Deep Learning” and “NVIDIA GRID”. Google was part of the keynote and it was very interesting seeing how far AI is evolving, Elon Musk the guy behind Tesla, Space-X was also on stage.

NVIDIA GRID was big this year and all the vendors, Lenovo, HP, Dell, Cisco, Supermicro, Citrix, Vmware and such was there. There was tonz of success stories and best practices. So amazing to learn all the best on GPU enabled application/desktop using either Citrix or VMware, this is the conference to learn from people that are early adapters, the best of the best. If you feel missed out come next year and you understand what I mean. This conference is very different compared to other conferences. This is here it all happens, all industries meet and make a fusion across GPU’s. If you missed this year GTC, I highly recommend you go to the next year GTC which takes place in April 4-8th, 2016 in Silicon Valley

I have captured some of the best moments

Great meeting Lakeside Software and seeing they had the “print” of the case study I did with Magnar Johnsen we did for Firstpoint client AIBEL.

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I meet for the first time the CEO and founder of NVIDIA Jen-Hsun Huang, he is a very inspiring person.

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Another great friend was Fred Devoir from Textron “the man in the middle” and another great friend and fellow CTP, Dane Young.

Fred Devoir had two sessions at GTC, I highly recommend you watch them both.

If you attended and could see all the sessions or you couldn’t join GTC, now all 500 sessions are available for the public. #AMAZING, thank you NVIDIA for this.

I have in this blogpost made it easy to find all the great sessions about NVIDIA GRID

Learn the best of the best about NVIDIA GRID implementations:

If you want to Watch the session I did at NVIDIA GTC click here

Click the sessions with the “blue” link and the recorded session will start.

Citrix sessions

 

Gunnar Berger, CTO from Citrix
S5872 – Worlds Collide: What Happens When VDI Meets GPU? 

Derek Thorslund, Director of Product Management, HDX, Citrix Systems
Mayunk Jain, Senior Technical Marketing Manager, Citrix Systems
S5390 – Citrix HDX 3D Virtualization: Six Years of Remoting 3D Apps

Roland Wartenberg Director Global SAP Alliance, Citrix
David Cruickshank Sr. Director, Strategy and Operations, SAP Co-Innovation Lab, SAP Labs
S5377 – Running SAP 3D Visual Enterprise Using Citrix and NVIDIA – What about Performance?

Erik Bohnhorst, SR. GRID Solution Architect from NVIDIA
Ronald Grass, SR. Systems Engineer from Citrix

S5393 – Evolution of an NVIDIA GRID™ Deployment

 

Citrix customer success stories:

Success story – Ford Motor Company

Chip Charnley, Technical Expert from Ford Motor Company
S5206 – So You Want to Deploy High Resolution Graphics Desktop Virtualization

Success story – Roger Williams University

George Thornton, VP of Engineering from Logical Front
Jim Galib IT Director from Roger Williams University
Ryan Tiebout, System Operations Manager from Rogers Williams University

S5225 – University’s Desktop Virtualization Delivers Graphics-Intense Apps on Any Device

Success story – Duke University

G Allan Johnson Charles E Putman Professor of Radiology,Physics, and Engineering from Duke University

S5558 – Publishing Medical Image Studies with NVIDIA GRID™

Success story – Georgia Institute of Technology College of Engineering

Florian Becker Sr. Director, Strategic Alliances, Lakeside Software

Didier Contis Director Technology Services, Georgia Institute of Technology College of Engineering

S5128 – Case Study: Georgia Tech Uses Citrix XenApp with NVIDIA® GRID™ to Deliver Engineering Applications

Success story – Textron

Fred Devoir Sr. Architect, Textron Inc.
Randall Siggers Solutions Architect, Textron Inc.

S5485 – Exploring Design Considerations: CAD/CAM Experiences from the Experts Using Citrix and VMware

Success story – The Kanavel Group

Garrett Taylor CIO, The Kanavel Group

S5620 – Implementing NVIDIA GRID with XenDesktop: A Technical Deep Dive


VMware sessions

Mark Margevicius Director, EUC Strategy, VMWare

S5533 – Dedicating GPUs for VDI and SBC Workloads: How the ROI and Business Value More Than Justifies the Expense

Banit Agrawal Senior Performance Engineer, VMware
Luke Wignall GRID Performance Engineering Manager, NVIDIA
Lan Vu Performance Engineer, VMware

S5385 – Benchmarking 3D workloads at scale on NVIDIA GRID with Horizon View 6 using View Planner

Jeff Weiss NVIDIA GRID SA Manager, NVIDIA
Luke Wignall GRID Performance Engineering Manager, NVIDIA

S5405 – VMware Horizon 6 and NVIDIA vGPU: Installation and Configuration Best Practices

VMware customer success stories

Success story – Jacobs Engineering

Jeff Weiss NVIDIA GRID SA Manager, NVIDIA
Randall Siggers Solutions Architect, Textron Inc.
Ali Rizvi PLM Support Analyst, Bell Helicopter

S5345 – VMware Horizon 6 View with NVIDIA GRID: A Practical Discussion of a Real-World Deployment

Success story – USC Information Sciences Institute

John Paul Walters Project Leader, USC Information Sciences Institute

S5323 – Achieving Near-Native GPU Performance in the Cloud
Download PDF of presentation

Success story – HDR Inc

Clint Pearson IT Infrastructure Systems Lead, HDR, Inc.
Jeremy Korell IT Infrastructure Systems Lead, HDR, Inc.

S5414 – GPU-Enabled VDI and Rendering at Architecture and Engineering Firm HDR

Vendors (HP, Cisco, Lakeside Software)

System Integrators of NVIDIA GRID


 System Integrators success stories of NVIDIA GRID

Success story – Poppelgaard.com

Thomas Poppelgaard, Technology Evangelist from Poppelgaard.com

S5445 – Building the Best User Experience with Citrix XenApp & NVIDIA® GRID™

Success story – PQR

Jits Langedijk, Senior Consultant from PQR

S5265 – Customer Success Story: Desktop Virtualization with NVIDIA GRID for a Large Construction Company

Success story – IMSCAD

Adam Jull CEO, IMSCAD

S5219 – Delivering Production Deployments Using Virtualization and NVIDIA GRID™

Success story – Wipro

Michael Harwood Citrix Architect, Wipro Limited

S5283 – Remote Visualization in Healthcare


Panel discussions

Aivars Apsite, Technology Strategist, Metro Health
Cedric Courteix, Partner Alliance Architect, VMware
Clint Pearson, IT Systems Lead, HDR Inc.
John Meza, Performance Engineering Team Lead, Esri

S5542 – Scaling Out Virtual GPU with NVIDIA GRID and VMware Horizon


NVIDIA sessions about Citrix & VMware

Jason Southern Senior Solution Architect, NVIDIA

S5213 – Effective Planning for Density and Performance in a Virtual Desktop Deployment with NVIDIA GRID™

Manvender Rawat GRID Applied Engineer, NVIDIA
Jason K Lee GRID Applied Engineer, NVIDIA

S5560 – Scalability Testing for Virtualized GPU Environments

Webinar I did with XenAppblog – “GPU in virtualization, learn why it’s important” now available

Hi All

I am very excited to share this great news with you all. I did a webinar with fellow CTP  Trond Eirik Håvarstein from XenAppBlog.com, and we had a special guest surprise Jeroen Van De Kamp CTP and CTO, LoginVSI announcing ground breaking stuff in the webinar. We had over 700 people signed up for the Webinar, if you was among the crowd that missed the opportunity to see the webinar here is your chance, the webinar is now available for everyone for free. There was a lot of Q/A and I will the next couple of days reply to all the Q/A and make them available in this article.

The webinar has been re-mastered and the audio & graphical demo videos is even better now  than in the actual webinar, make sure to check it out now:

Download the presentation here (PDF format)

Summary of webinar product announcements from LoginVSI, Lakeside Software, Uberagent for Splunk.

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LoginVSI upcoming new version support’s GPU benchmark…

LoginVSI is working on next version that will support benchmark, capacity planning, stress testing the “missing component in virtualization” GPU. If you are interested you can write to get access to the beta version of LoginVSI.

Here are some screen shots from the session…. watch it to here what Jeroen tells about the upcoming version

Note if you want to get more info on the next version of LoginVSI that supports GPU, write to info@loginvsi.com subject GFX

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Lakeside

Lakeside Software Monitoring/Assessing NVIDIA GRID

Another groundbreaking product announcement was from Lakeside Software, they are about to release version 7 of Systrack that will support NVIDIA GPU Monitoring/assessing.

Application Graphics Benchmarking

The transformation of an existing software portfolio first begins with the identification of all of the actively used software packages in the environment. The added complication in the case of a project to begin advanced application delivery is the need to understand multiple facets of usage: resource consumption, graphics utilization, frequency of use, user access habits, and mobility needs. Because the state of IT is already so complex it only becomes possible to fully understand and plan with a complete set of descriptive information that really characterizes the unique aspects of every environment. Of particular interest is the ability to first identify applications that have GPU demands, and then begin to segment them into tiers of utilization. SysTrack continually collects information about software packages as they’re used and normalizes all data points for cross platform comparison. One of the key performance parameters that’s identified in this process is a graphical intensity measure (Graphics Index) that provides a way to identify those applications in the portfolio that have higher GPU demands than others. With this critical information it becomes possible to segment the portfolio into groupings based on their requirements for specific resources. By tying a general sense of which applications have peak demand to total length of usage it becomes easier to start developing a portfolio made up of different combinations of usage styles. This includes separating applications that may be used by a small set of the population with intense requirements versus widely used applications with a smaller footprint. Of course, this also allows for much deeper analytics centering on the behaviors of users that is quite important in planning the GPU profiles in use in provisioning. Figure 1 displays this relationship in a bubble chart format, this format groups applications based on their similar characteristics presenting clusters of similar applications in larger bubbles. The vast majority of applications exist in the “low graphics demand – Low Time Active” area in the bottom left, while only a select few have either high graphics demand or high time active.

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SysTrackTracks graphics usage frequency across on physical clients and allows you to group users based on graphics usage & frequency

A natural expansion of this is grouping users into distinct workload types to understand how best to configure the profile types and GPU assignments for users. Once the target applications and users have been characterized and a plan has been developed it’s critical to begin the process of sizing the environment. This includes determining the architecture, sizing the desktops and servers that will be worked with, and identifying resources that will be required to support the needs of the planned deployment.

Resource Modeling & Capacity Planning

NVIDIA Marketplace report from Systrack’sVirtual Machine Planner (VMP) outlines the number of users that fall into different use cases making it easier to forecast how many users per board can be allocated

With a complete portfolio plan it now becomes possible to move into the next phase and start creating a model for what resources will be required for a complete environment. Because each of the users have been fully characterized throughout the assessment data collection interval it’s possible to use SysTrack’s Virtual Machine Planner (VMP) for powerful mathematical analysis to provide deep insight into infrastructure provisioning. The first component of this involves using the profile information above to help develop a plan for what kind of solution will be provided to the end-users. By segmenting the population into different delivery strategies using Citrix FlexCast options as a guideline, a more complete and accurate picture of how the net new environment will operate can be created. An additional benefit of segmentation is the ability to take advantage of grouping by general graphics consumption to identify the number of GPUs required for the environment based on the user density information for each profile type

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The NVIDIA MarketPlace report from VMP outlines the number of users that fall into the various use cases (e.g. “high” for a designer or higher end power user), making it much easier to forecast how many users per board can be allocated and in turn how many total boards may be needed

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This information creates an easy to use design for a set of user profiles, both for the actual desktop delivery and for the vGPU assignment. By ensuring the best possible analysis of the environment prior to the actual deployment the end-user experience is much simpler to forecast and control. This results in higher end-user satisfaction and a shorter transition time.

User Experience Optimization

After the successful implementation of the solution the environment still requires observation to prevent interruption of service and the potential for productivity impact. The best way to ensure optimal end-user service quality is to have a real-time alerting and analytical engine to collect and report instantly on degradation of any aspect of the systems the users interact with. SysTrack provides this in the form of proactive alerting, detailed system analysis in Resolve, and aggregate trending through Enterprise and Site Visualizer. An even more interesting feature is vScape, a tool designed to examine utilization across multiple virtual machines and correlate resource consumption to concurrency of application utilization. vScape provides real-time updates of all of the application usage across all virtual platforms in an enterprise, including information about what applications are currently demanding GPU resources. It also provides insight into other resource demands as well, such as CPU, memory, and I/O. This can help automate the discovery of co-scheduled or highly concurrent applications to pinpoint the root cause of oversubscription issues much more quickly. It also provides key insight into guest health characteristics with trending to correlate precisely which events may lead to service degradation

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Another key feature introduced in SysTrack version 7.0 is the result of close collaboration with NVIDIA to leverage APIs presented in the guest operating system. This allows the capture of detailed GPU performance metrics to correlate vGPU consumption to end-user service quality. Specifically, with NVIDIA drivers present in the guest OS or on a physical system, the GPU utilization and key metrics (see table 2 for a sample of selected metrics) from the graphics card can be captured and analyzed in the same way as CPU or other system metrics are currently in SysTrack.

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In Systrack 7 after provisioning users in VDI environment the IT admins can monitors performance, which enables to optimize density over time.

This completes the set of KPIs used in SysTrack to calculate the end-user experience score, including categories like resource limitation, network configuration, latency, guest configuration, protocol specific data for ICA, and virtual infrastructure. With a complete set of relevant information the proactive and trending health analysis provided in SysTrack yields a thorough analysis in an easy to understand, quantitative score that summarizes performance on an environmental, group based, or individual system level.

NVIDIA GPU Monitoring/Assessing: (Works with all NVIDIA GPU) Quadro, Kepler, GRID

 

You will be able to look at following parameters:

  • Device ID
  • Power State
  • GPU Usage
  • Frame Buffer Usage
  • Video Usage
  • Bus Usage
  • Memory Usage (Bytes and Percent)
  • # of Apps
  • Temperatures and Fan RPMS

Use this data to accurately plan and size GRID and HDX 3D Pro deployments based on actually observed usage and utilization.

Monitor users post-deployment to provide the best user experience

I recommend reading the whitepaper Lakeside Software have created:
White Paper: SysTrack Delivery Optimization and Planning for NVIDIA GRID and Citrix HDX

 

uberagent

UberAgent 1.8 for Splunk adds GPU performance monitoring

Helge Klein have developed a new version of Splunk that now supports monitoring of GPU, this was a feature request I talked with Helge Klein about in 2013, and I am so happy to see the results what he have done with UberAgent for Splunk, lets dig in what it can do.

uberAgent measures:

  • GPU compute usage per machine
  • GPU memory usage per machine
  • GPU compute usage per process
  • GPU memory usage per process
  • uberAgent shows memory usage separately for shared and dedicated memory (dedicated = on the GPU, shared = main system RAM)
  • uberAgent shows compute usage per GPU engine. The various GPU engines serve different functions, e.g. 2D acceleration, 3D acceleration, video decoding, etc.

uberAgent - process GPU usage uberAgent - single machine GPU usage over time uberAgent - single process GPU usage over time uberAgent - machine GPU usage

For more information visit uberAgent’s website.

My 5 cents

I am very excited to share my findings of some of the things I do in poppelgaard professional services. Feel welcome to contact me at thomas@poppelgaard.com if you are interested in using my professional services and you need help with GPU solutions.

You will see more upcoming blogs from me covering this topic. End User experience, assessments of GPU workload, scaling/sizing, benchmarking, hardware supported, GPU side by side experience, Hypervisor vs Bare metal with a GPU. Watch out for cool things….

Source

Watch the webinar here (YouTube)
Download the presentation here (PDF format)

Lakeside Software
LoginVSI
White Paper: 
SysTrack Delivery Optimization and Planning for NVIDIA GRID and Citrix HDX
UberAgent for Splunk

Citrix XenDesktop HDX3D Pro
Citrix XenApp with GPU Sharing
Citrix XenServer vGPU
NVIDIA GRID
AMD FirePro
VMware vSphere vDGA
VMware vSphere vSGA with NVIDIA GRID