(lively music)
>> Narrator: Live, from San Francisco,
celebrating 10 years of high tech coverage,
it's theCUBE,
covering VMworld 2019!
Brought to you by VMware and its ecosystem partners.
>> Okay, welcome back to theCUBE's live coverage
in VMworld 2019.
We're in San Francisco.
We're in Moscone North Lobby.
I'm John Frer, my co Stu Miniman,
here covering all the action of VMworld,
two sets for theCUBE, our tenth year, Stu.
Keeping it going.
Two great guests, John Fanelli, CUBE Alumni,
Vice President of Product, Virtual GPUs at NVIDIA
Kevin Gray, Director of Product Marketing, Dell EMC.
Thanks for coming back on.
Good to see you.
>> Awesome. >> Good to see you guys, too.
>> NVIDIA, big news, we saw your CEO up
on the keynote videoing in.
Two big announcements.
You got some stats on
some Windows stats to talk about.
Let's talk about the news first,
get the news out of the way.
>> Sure, at this show, NVIDIA announced
our new product called NVIDIA Virtual Compute Server.
So for the very first time anywhere,
we're able to virtualize artificial intelligence,
deep learning, machine learning, and data analytics.
Of course, we did that in conjunction
with our partner, VMware.
This runs on top of vSphere
and also in conjunction with our partner at Dell.
All of this Virtual Compute Server runs on
Dell VxRail, as well.
>> What's the impact going to be for that?
What does that mean for the customers?
>> For customers, it's really going to be the on-ramp
for Enterprise AI.
A lot of customers, let's say they have a team
of maybe eight data scientists are doing data analytics,
if they want to move through GPU today,
they have to buy eight GPUs.
However, with our new solution,
maybe they start with two GPUs
and put four users on a GPU.
Then as their models get bigger
and their data gets bigger,
they move to one user per GPU.
Then ultimately, because we support multiple GPUs now
as part of this, they move to a VM
that has maybe four GPUs in it.
We allow the enterprise
to start to move on to AI and deep learning,
in particular, machine learning
for data analytics very easily.
>> GPUs are in high demand.
My son always wants the next NVIDIA,
in part told me to get some GPUs from you
when you came on.
Ask the NVIDIA guy to get some for his gaming rig.
Kidding aside, now in the enterprise,
really important around some of the data crunching,
this has really been a great use case.
Talk about how that's changed,
how people think about it,
and how it's impacted traditional enterprise.
>> From a data analytics perspective,
the data scientists will ingest data,
they'll run some machine learning on it,
they'll create an inference model
that they run to drive predictive business decisions.
What we've done is we've GPU-accelerated
the key libraries, the technologies,
like PyTorch, XGBoost to use a GPU.
The first announcement is about how they can now use
Virtual Compute Server to do that.
The second announcement is that workflow is,
as I mentioned, they'll start small,
and then they'll do bigger models,
and eventually they want to train that scale.
So what they want to do is they want to move to the cloud
so they can have hundreds or thousands of GPUs.
The second announcement is that NVIDIA
and VMware are bringing Virtual Compute Server
to VMware Cloud running on AWS
with our T4 GPUs.
So now I can scale virtually starting with fractional GPU
to single GPU to multi GPU,
and push a button with HCX
and move it directly into AWS T4 accelerated cloud.
>> That's the roadmap so you can get in,
get the work done, scale up,
that's the benefit of that.
Availability, timing,
when all of this is going to hit in--
>> So Virtual Compute Server is available
on Friday, the 29th.
We're looking at mid next year for the full suite
of VMware Cloud on top of Aws T4.
>> Kevin, you guys are supplier here at Dell EMC.
What's the positioning there with you guys?
>> We're working very closely with NVIDIA in general
on all of their efforts around both AI
as well as VDI too.
We'll work quite a bit,
most recently on the VDI front as well.
We look to
drive things like qualifying the devices.
There's both VDI or analytics applications.
>> Kevin, bring us up-to-date
'cause it's funny we were talking about this is
our 10th year here at the show.
I remember sitting across
Howard Street here in 2010
and Dell, and HP, and IBM all claiming who had
the lowest dollar per desktop
as to what they were doing in VDI.
It's a way different discussion here in 2019.
>> Absolutely.
Go ahead.
>> One of the things that we've learned with NVIDIA is that
it's really about the user experience.
It's funny we're at a transition point now
from Windows 7 to Windows 10.
The last transition was Windows XP to Windows 7.
What we did then is we took Windows 7,
we tore everything out of it we possibly could,
we made it look like XP,
and we shoved it out.
10 years later, that doesn't work.
Everyone's got their iPhones, their iOS devices,
their Android devices.
Microsoft's done a great job on Windows 10 being immersive.
Now we're focused on user experience.
When the VDI environment, as you move to Windows 10,
you may not be aware of this,
but from Windows 7 to Windows 10,
it uses 50% more CPU,
and you don't even get that great of a user experience.
You pop a GPU in there, and you're good.
Most of our customers together are working
on a five-year life cycle.
That means over the next five years,
they're going to get 10 updates of Windows 10,
and they're going to get like 60 updates
of their Office applications.
That means that they want to be future-proof now
by putting the GPUs in to guarantee a great user experience.
>> On the performance side too, obviously.
In auto updates, this is the push notification world
we live in.
This has to built in from day one.
>> Absolutely, and if you look at what Dell's doing,
we really built this into both our VxRails
and our VxBlocks.
GPUs are just now part of it.
We do these fully qualified.
It stacks specifically for VDI environments as well.
We're working a lot with the n-vector tools from VM
which makes sure we're-- >> VDI finally made it!
>> qualifying user experience.
>> All these years.
>> Yes, yes.
In fact, we have this user experience tool called n-vector,
which actually, without getting super technical
for the audience, it allows you to look
at the user experience based on frame-rate,
latency, and image quality.
We put this tool together,
but Dell has really been taking a lead
on testing it and promoting it to the users
to really drive the cost-effectiveness.
It still is about the dollar per desktop,
but it's the dollar per dazzling desktop.
(laughing)
>> Kevin, I hear the frame-rate in there,
and I've got all the remote workers,
and you're saying how do I make sure
that's not the gaming platform they're using
because I know how important that is.
>> Absolutely.
There's a ton of customers that are
out there that we're using.
We look at folks like Guillevin
as like the example of a company
that's worked with us
and NVIDIA to truly drive types of applications
that are essential to VDI.
These types of power workers doing applications
like Autodesk, that user experience
and that ability to support multiple users.
If you look at Pat, he talked a little bit about
any cloud, any application, any device.
In VDI, that's really what it's about,
allowing those workers to come together.
>> I think the thing that the two of you mentioned,
and Stu you pointed out brilliantly was that
VDI is not just an IT thing anymore.
It really is the expectation now that my rig,
if I'm a gamer, or a young person,
the younger kids, if you're under 25,
if you don't have a kick-ass rig,
(laughs) that's what they call it.
Multiple monitors, that's the expectation,
again, mobility.
Work experience, workspace.
>> Exactly, along those same lines, by the way.
>> This is the whole category.
It's not just like a VDI, this thing over here
that used to be talked about as an IT thing.
>> It's about the workflow.
So it's how do I get my job done.
We used to use words like "business worker"
and "knowledge worker."
It's just I'm a worker.
Everybody today uses their phone that's mobile.
They use their computer at home,
they use their computer at work.
They're all running with dual monitors.
Dual monitors, sometimes dual 4K monitors.
That really benefits as well from having a GPU.
I know we're on TV so hopefully some of you guys are
watching VDI on your GPU-accelerated.
It's things like Skype, WebEX, Zoom,
all the collaboration to 'em, Microsoft Teams,
they all benefit from our joint solution, like the GPU.
>> These new subsystems like GPUs become so critical.
They're not just subsystem,
they are the main part because the offload is now part
of the new operating environment.
>> We optimized together jointly using the n-vector tool.
We optimized the server and operating environment,
so that if you run into GPU,
you can right-size your CPU in terms of cores, speed, etc.,
so that you get the best user experience
at a most cost effective way.
>> Also, the gaming world helps
bring in the new kind of cool visualization.
That's going to move into just the workflow of workers.
You start to see this immersive experience,
VR, ARs obviously around the corner.
It's only going to get more complex,
more needs for GPUs.
>> Yes, in fact, we're seeing more, I think, requirements
for AR and VR from business than we are actually for gaming.
Don't you want to go into your auto showroom at your house
and feel the fine Corinthian leather?
>> We got to upgrade our CUBE game,
get more GPU focused and get some tracing in there.
>> Kevin, I know I've seen things from the Dell family
on levering VR in the enterprise space.
>> Oh, absolutely.
If you look at a lot of the things that we're doing
with some of the telcos around 5G.
They're very interested in VR and AR.
Those are areas that'll continue to use
things like GPUs to help accelerate
those types of applications.
It really does come down to having
that scalable infrastructure that's easy to manage
and easy to operate.
That's where I think the partnership with NVIDIA
really comes together.
>> Deep learning and all this stuff around data.
Michael Dell always comes on theCUBE, talks about it.
He sees data as the biggest opportunity and challenge.
In whatever applications coming in,
you got to be able to pound into that data.
That's where AI's really shown...
Machine learning has kind of shown that
that's helping heavy lifting a lot of things
that were either manual.
>> Exactly.
The one thing that's really great about data analytics
that are GPU-accelerated is we can take a job
that used to take days and bring it down to hours.
Obviously, doing something faster is great,
but if I take a job that used to take a week
and I can do it in one day,
that means I have four more days
to do other things.
It's almost like I'm hiring people for free
because I get four more extra work days.
The other thing that's really interesting
as our joint solution is you can leverage
that same virtual GPU technology.
You can do VDI by day
and at night, you run Compute.
So when your users aren't at work,
you migrate them off,
you spin up your VMs that are doing your data analytics
using our RAPIDS technology,
and then you're able to get
that platform running 24 by seven.
>> Productivity gains just from an infrastructure.
Even the user too, up and down,
the productivity gains are significant.
So I'll get three monitors now.
I'm going to get one of those Alienware curved monitors.
>> Just the difference we had,
we have a suite here at the show,
and just the difference, you can see such a difference
when you insert the GPUs into the platform.
It's just makes all the difference.
>> John, I got to ask you a personal question.
How many times have people asked you for a GPU?
You must get that all the time?
>> We do.
I have a NVIDIA backpack.
When I walk around, there's a lot of people
that only know NVIDIA for games.
So random people will always ask for that.
>> I've got two sons and two daughters
and they just nerd out on the GPUs.
>> I think he's trying to get me to commit on camera
on giving him a GPU.
(laughing) I think I'm in trouble here.
>> Yeah, they get the latest and greatest.
Any new stuff, they're going to be happy
to be the first on the block to get the GPU.
It's certainly impacted on the infrastructure side,
the components, the operating environment, Windows 10.
Any other data you guys have to share
that you think is notable around
how all this is coming together
working from user experience around Windows and VDI?
>> I think one piece of data,
again, going back to your first comment
about cost per desktop.
We're seeing a lot of migration to Windows 10.
Customers are buying our joint solution from Dell
which includes our hardware and software.
They're buying that five-year life cycle,
so we actually put a program in place
to really drive down the cost.
It's literally like $3 per month
to have a GPU-accelerated virtual desktop.
It's really great Value for the customers
besides the great productivity.
>> If you look at doing some of these workloads on premises,
some of the costs can come down.
We had a recent study around the VxBlock as an example.
We showed that running GPUs
and VDI can be up as much as 45% less on a VxBlock at scale.
When you talk about the whole hybrid cloud,
multi-cloud strategy, there's pluses and minuses to both.
Certainly, if we look at some of the ability to start small
and scale out, whether you're going HCI
or you're going CI, I think there's a VDI solution there
that can really drive the economics.
>> The intense workloads.
Is there any industries that are key for you guys
in terms of verticals?
>> Absolutely.
So we're definitely looking at a lot
of the CAD/CAM industries.
We just did a certification on our platforms
with Dassault's CATIA system.
That's an area that we'll continue to explore
as we move forward.
>> I think in the workstation side of things,
it's all the standard, it's automotive,
it's manufacturing.
Architecture is interesting.
Architecture is one of those companies
that has kind of an S and B profile.
They have lots of offices,
but they have enterprise requirements
for all the hard work that they do.
Then with VDI, we're very strong in financial services
as well as healthcare.
In fact, if you haven't seen, you should come by.
We have a Bloomberg demo for financial services
about the impact for traders.
I have a virtualized GPU desktop.
>> The speed is critical for them.
Final question.
Take-aways from the show this year,
2019 VMworld, Stu, we got 10 years to look back,
but guys, take-aways from the show
that you're going to take back from this week.
>> I think there's still a lot of interest and enthusiasm.
Surprisingly, there's still a lot of customers
that haven't finished there migration to Windows 10
and they're coming to us saying,
Oh my gosh, I only have until January,
what can you do to help me?
(laughing)
>> Get some GPUs.
Thoughts from the show.
>> The multi-cloud world continues to evolve,
the continued partnerships that emerge as part of this is
just pretty amazing in how that's changing
in things like virtual GPUs and accelerators.
That experience that people have come to expect
from the cloud is something, for me is a take-away.
>> John Fanelli, NVIDIA, thanks for coming on.
Congratulations on all the success.
Kevin, Dell EMC, thanks for coming on.
>> Thank you.
>> Thanks for the insights.
Here on theCUBE, Vmworld 2019.
John Furrier, Stu Miniman, stay with us
for more live coverage after this short break.
(lively music)