NVIDIA Community Advisor Program – deadline June 15th 2016 – seeking more diverse candidates!

nvidiadiverse
NVIDIA has a good record on corporate diversity metrics

NVIDIA recently announced an Enterprise Community Advisor program (initially focused on the GRID and virtualized products). Applications for this remain open until Midnight (UK time) on 15th June 2016. So still plenty of time to apply! You can read the program announcement and details on how to apply here: https://blogs.nvidia.com/blog/2016/04/04/nvidia-grid/

To date we have over 30 applications of which 1 is female and 2 not from North America or _Northern_ EMEA (Scandinavia, UK, Germany, Netherlands, etc)….While applications will only be assessed on pure technical merit/experience to the criteria on the application form (see here: https://docs.google.com/forms/d/15EZEfjrR28ofHd8FU7lWWoiR_KETx-0mzy6an_ng424/viewform), I had hoped we’d have a more diverse gender and geographical set of candidates and I’m not sure why we don’t.

The lack of female candidates

This was not a huge surprise. I don’t come across many women working in virtualization or on the technical/practical side of professional virtualized graphics. A similar advisor program launched by partner Atlantis announced an initial cohort of 28 Virtualisation and Storage experts – all male and mostly North American and Northern European: http://www.atlantiscomputing.com/pr_2016_04_26_atlantis-computing-expands-atlantis-community-experts-program. It’s also only in the last year or so that Citrix’s CTP 50 member strong program has had any female professionals (now 4).

Why virtualization seems particularly low on women compared to many areas of IT I’ve never fully worked out thought…. ???

The lack of candidates from other geographies

This is more puzzling as I come across huge numbers of NVIDIA GRID users, partners and experts in regions and countries such as Brazil, China, Russia, Japan, ANZ, India and Southern and Eastern Europe. So I’m racking my brains for reason as to why candidates haven’t emerged from these regions, mooting possibilities such as:

  • Language barriers
  • Not advertising in the right places – are mine and the @NVIDIAGRID teams social streams to USA and EMEA focussed
  • Obstacles to travel / involvement
  • Culturally community programs don’t align well with business practices / culture

Should I worry? Have I done enough to ensure potential qualified candidates know about the program?

If candidates don’t apply you can’t consider them, is it that they don’t exist or am I just not reaching them…. Thoughts?

Could Deep Learning find the needle in the PDM/PLM haystacks or cloud?

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Yowza at D3Live 2016!

Recently I attended the NVIDIA GTC Developers’ conference and spent a little time learning more about the deep learning products. A branch of machine learning that often aims to make better representations and create models to learn these representations from large-scale unlabeled data. Many of the use cases have been associated with text and image search, facial recognition or medical diagnosis (identifying specific cancers, medical problems).

Deep learning is a very generic (in the broad-reaching sense) technology, companies like NVIDIA have developed the GPU technology and on top of them frameworks have been built to allow researchers and developers to rapidly construct products without actually developing bespoke image recognition technologies or similar. At GTC we had a bit of an employee hackathon and a group of our staff with no experience or machine-learning background built a solution to classify whale songs in an afternoon. Supplied with the data set from a kaggle competition and a framework it was apparently fairly straightforward (http://danielnouri.org/notes/2014/01/10/using-deep-learning-to-listen-for-whales/).

Coming from a CAD/CAE/PLM background the perfect application in my mind for this type of technology is part recognition and PDM (product Data Management). For every designer actually using Siemens NX or Dassault Solidworks/Catia there is a vast ecosystem of engineering users using and sharing the CAD data via PDM/PLM applications such as Enovia, Delmia, Teamcenter or cloud collaboration tools.

CAD is undoubtably getting cloudy – with onshape, outscale, fra.me and GrabCAD as well as numerous VDI users using VMware/Citrix etc. CAD though always carries a lot of legacy constraints and you have to deal with what you’ve got. The PDM/PLM and indeed BIM (in AEC) communities spend vast amounts of effort on part labelling conventions, search and part translation. Basically trying to find out what they’ve already got! (You only have to read the main PLM/PDM blogs such as Oleg Shilovitsky – see: http://beyondplm.com/2015/11/04/intelligent-part-numbers-might-be-a-good-idea-in-connected-world/ to see the PDM/PLM folk spend a lot of time and effort indexing and trying to find their parts!)

So how do you find stuff

There are a few 3D CAD search technologies around but strangely whilst everyone is talking about putting stuff in the cloud and sharing these technologies don’t seem to get much press.

Many products use some of the features and techniques outline in this seminal paper: https://www.uni-konstanz.de/mmsp/pubsys/publishedFiles/BuKeSa06.pdf; and use one or more of the techniques to make a very lightweight “fingerprint” of the CAD part and then look for sections of that fingerprint: same size, same hole pattern, material attributes (bits of metadata on part), sometimes you want same part but rescaled, could be re-oriented/affine transform etc ….

 

Companies/products I’ve come across in the 3D search space:

This isn’t a space I’ve followed particularly closely for a few years but I suspect it might finally be getting some end-user traction and visibility. As more and more folk put stuff in the cloud and datacenter the need to find it again over ever more disperse infrastructure grows!

  • Geolus (Siemens PLM); Geolus must be a decade old or more. When I worked at Siemens they fascinated me and I never understood why this gem was never more promoted amongst the vast range of Siemens portfolio. I guess with so many technologies the exciting cooler ones that would be the VCs/start-ups sparkle are simply taken for granted? Mature and established in use in many vast real manufacturers that are Siemens bread-and-butter.
  • Cadenas; This has always been a fascinating company, a German CAD parts catalogue rather than a modeler. Quietly for many years they have been developing simply very interesting technologies. They added some degree of modelling capability allowing a designer to define a simplified part against which to search. Partnered with more familiar names e.g. Delcam (now Autodesk) and won some serious acclaim from the manufacturing sector. Novel technologies being built on-top of a real established traditional CAD business, slowly and steadily.
  • ShapeSpace – made a fair amount of impact in 2013 and got some good partners but seem to have gone quiet recently, a small UK software company I’m not quite sure what they are up to currently.
  • Yowza; Where did they come from? Established in just 2015, this year they made a splash at Develop3D live, with a polished booth, talks and demos. Of all the companies I am familiar with in the 3D/CAD search.

Financial drivers

There are huge financial drivers for decent CAD search and categorization:

So where is Deep Learning?

Now this is where it got a bit disappointing. It seemed such a natural match of technology to problem and yet when I started googling I was surprised at the very limited material of the area. A few papers mainly behind pay-for (booo!!!) journal firewalls http://link.springer.com/article/10.1631%2Fjzus.C1300185

CAD / PLM does tend to be a closed industry. The bucks are big in PLM and many technologies are developed in-house and the expertise kept in house. Although many of the big players license their components and APIs (e.g. Geolus and Parasolid from Siemens), you won’t find a developer community or information on the technologies lying around the internet.

So will we see deep-learning in the CAD / BIM headlines soon? My guess is probably not, my feeling is that this type of technology will creep in behind the scenes.

Although with start-ups like Yowza popping up at end-user events like D3DLive! Perhaps there will be a little disruption and end-user interest in the overlooked area of CAD indexing/part retrieval.

 

Learn more:

 

NVIDIA GRID GPUs perfect for keeping up with the Raspberry Pi and the next generation of end points

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Citrix have been making a fair bit of noise about their end-client (Receiver) being available and supported in-conjunction with partner ThinLinx on the Raspberry Pi, which with peripherals is proving a sub-$100 thin-client, capable of handling demanding graphics and frame rates (fps) of 30fps or more (YouTube is usually 30fps).

The Raspberry Pi and other low-cost end-points such as the Intel NUC are capable because they support hardware decode of protocols such as H.264 and JPEG used by HDX/ICA, they have SoC (system on a chip) hardware designed to handle graphics really very well.

There has been a lot of excitement in the industry and community, with traditional thin-clients typically costing $300-$600 the Pi offers potential cost savings but also the opportunity to use VDI/Application remoting (XenDesktop or XenApp) in scenarios where it wouldn’t have made financial sense.

There have been some stunning videos demonstrating the potential of this new class of low-cost endpoint such as:

And what do all these videos have in common – THEY WERE ALL RECORDED USING SERVERS BACKED BY NVIDIA GRID virtualized GPUs (vGPU or GPU-sharing via XenApp and GPU pass-through)! Because:

  • If you have effective hardware decode on the client you need your server to be able to keep up and pump out high frame rates and visual quality
  • With low cost clients virtualized (shared vGPU or XenApp GPU-sharing via passthrough) offers a cost effective way to boost the graphical power of the server without the need for a dedicated GPU per user

The Citrix Pi project highlights the power of using hardware encode and decode on GPUs. With the GPU able to take the brunt of the workload leading to:

  • Battery and power savings
  • The opportunity to offload server CPU for the protocol encode on the server boosting scalability, whilst Citrix only currently have hardware encode for their Linux VDA. With VMware Blast Extreme and NICE already offering it. The opportunity for NVIDIA GRID customers to see future value, as Citrix catches up, are there. The Pi project and VMware / NICE developments are vindication that this is where the industry is going – there are simply many tasks associated with virtualizing graphics that GPUs are best suited to.
  • Tests with blast extreme and NVENC shows up to 51ms lower latency on screen updates and lower CPU usage http://blogs.vmware.com/euc/2016/02/vmware-horizon-blast-extreme-acceleration-with-nvidia-grid.html so the potential for Citrix to emulate is clear.

Savings on the end-client costs is likely to change the balance of VDI deployment costs, allowing customers to invest more in the server data centre and freeing up budget for GPUs to access the user-experience improvements, benefits of consolidation and power savings. It really doesn’t make sense to have high-end workstations or PCs dotted around remote locations in use for a few hours a day for many customers anymore.

Once you get GPUs into a data centre, many sys admins report a reduction in costs associated with sluggish performance and  helpdesk calls. It’s not just high-end graphics benefit from GPU-acceleration but regular office applications, browsers and unified communications (Cisco Jabber, Skype, etc). You can read more here: https://www.virtualexperience.no/2015/11/05/mythbusting-browser-gpu-usage-on-xenapp/ and also here: https://www.citrix.com/blogs/2015/12/03/gpu-for-the-masses-with-xenappxendesktop/.

Exciting times! I somehow suspect we’ll see Citrix make (quite rightly) quite a bit of fuss over the Pi at their upcoming Synergy event! A performant end-client though needs to be fed by a performant server and NVIDIA GRID is a great match.

More Info:

NVIDIA GRID: New knowledge resources – just released!

KB2The NVIDIA Knowledge base is going from strength to strength.  Since GRID moved to a software and fully-supported enterprise model there has been an acceleration in the information being published there that should carry on long-term.

Known issues, workarounds, how-to-guides and links to other places to find information on NVIDIA products including GRID and vGPU.

Yet MORE NEW articles have just been released:

NEW KB Articles – this week!

NEW KB Articles – last week

As always I’d recommend a visit to the GRID user forums where you can ask questions with the users who include customers, partners and NVIDIA staff including developers who write the product and support staff: Have a look – HERE!

Where to find the drivers for NVIDIA GRID 2.0 vGPU and up, including M60 and M6 drivers

Quick blog, to highlight where you get GRID vGPU drivers and software for GRID 2.0 and higher. Whilst unsupported older products are available on the general NVIDIA download sites, newer products need to be obtained via the NVIDIA enterprise licensing portal.

Customers of GRID 2.0 and up NVIDIA products should receive access to an NVIDIA licensing portal account. Drivers for the GRID GPU cards such as the M6 and M60 can be obtained via this portal.

Two types of customers: 90 days evaluation (pre-sales), and paying customers

Evaluation Customers

  1. Go to www.nvidia.com/grideval
  2. Click “software download”
  3. Fill in registration form
  4. Get access to the NVIDIA licensing portal that will let you download 128 evaluation licenses and GRID software.

 Paying Customers

  1. The process is documented here: http://images.nvidia.com/content/pdf/grid/guides/quickstartguide.pdf
  2. But just to capture the summary from this documentation
  • When you purchase GRID, you receive email with PAK and registration link to the licensing portal.
  • When you login to the portal, you get access to download all the licenses you have purchased along with GRID software.

Relevant Products:

Enterprise supported GRID vGPU drivers including M60 and M6 GPUs

VMWorld 2016 – VMware let users set the agenda! Go VMware!

VMware Democracy at VMworld – it seems you can vote for what sessions you’d like to see. I think this is a super idea as it allows the community, partners and customers to actually pre-screen the balance of talks and speakers.

This kind of openness where VMworld lets their community see what has been submitted (and subsequently rejected/accepted) is great. It allows others to be aware of potential speakers who whilst might not be suitable for VMworld may fit other events/platforms better. It’s also a very strong message that this conference is for the users. Go VMware!

I wish more conferences did this.

How-to-vote

  • From now till May 24th you will be able to cast your vote on the 1500+ submissions that came in through the Call for Papers. To VOTE, go to http://www.vmworld.com/en/call-for-papers.html log into your account – just click the “like” button and you’ve cast your vote.
  • Public Session Voting is the opportunity for the VMware community of experts, customers, partners, bloggers and enthusiasts to cast their votes and help shape the agenda for VMworld 2016.

Session Voting is open to everyone and anyone. You will be required to login to your vmworld.com account. If you do not have a vmworld.com account, you can set one up for free.

 

NVIDIA GRID at VMworld

If you are interested in seeing sessions on NVIDIA GRID and vGPU, just search on key words like “NVIDIA” and “vGPU”. Some of the submissions I know of include:

  • Title: Why does Siemens use High-Performance Desktops with VMware Horizon and NVIDIA GRID – Submission from Soeren Reinersen, Siemens Wind VMware ,  Sarah Mannion NVIDIA, ID: 7888
  • Title: Sizing your NVIDIA GRID with VMware Horizon 7 – Submission from: Erik Bohnhorst, NVIDIA, ID: 8211
  • Title: Accelerating VMware Horizon Blast Extreme with NVIDIA GRID – Submission from: Erik Bohnhorst NVIDIA, ID: 7517
  • Title: Selecting the right NVIDIA GRID edition with VMware Horizon – Submission from: Manvender Rawat, NVIDIA ID: 8232
  • Title: A Technical Deep Dive on Performance, Scalability and Deployment Best Practices of GPU-accelerated workloads with VMware Horizon View and Nvidia GRID vGPU – Submission from: Lan Vu VMware and Manvender Rawat NVIDIA, ID: 8447
  • Title: Scientific Methodology to Determine User Experience for VDI – Submission from: Deepti Jain, NVIDIA, ID: 9202
  • Title: Customer Success at TSP: NVIDIA vGPU on Horizon View – Submission from: Jeff Weiss + NVIDIA Customer, ID: 8254
  • Title: NVIDIA vGPU on Horizon from Pilot to Production Deployment – Submission from: Jeff Weiss Submission ID: 8178
  • Title: Real world NVIDIA GRID vGPU sizing for optimized user experience with VMware vRealize – Submission from: Milan Diebel NVIDIA, ID: 8464
  • Title: How Architectural Design Firms Leverage Virtual GPU Technology for Global Collaboration – Submission from: Randall Siggers NVIDIA, ID: 9045

 

NVIDIA-GRID-vGPU-VMware-vSphereMany of these speakers have spoken at NVIDIA’s GTC events and recordings are available so you can get an idea of the expertise of the speakers and technical depth. See GTC-on-demand: HERE. Perhaps you have seen them and can comment below on sessions you are looking forward to at VMworld?

VMworld will be held on August 28 – Sept 1 2016 in Las Vegas. There is still time to sign-up.  If you’d like to find out more about our partnership with VMware – why not visit our community site; full of forums, FAQs, webinars and product overviews:

NVIDIA GRID Knowledge Base – New Articles

answers
Lots of answers and some fascinating tips and how-to-guides on NVIDIA GRID!

Have you visited the NVIDIA Knowledge base recently? Since GRID moved to a software and fully-supported enterprise model there has been an acceleration in the information being published there that should carry on long-term.

Known issues, workarounds, how-to-guides and links to other places to find information on NVIDIA products including GRID and vGPU. Continue reading NVIDIA GRID Knowledge Base – New Articles