 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, in North Lobby, I'm John Furrier, my co-student Miniman, here covering all the action of VMworld, two sets for theCUBE, our 10th year, keeping it going, two great guests, John Finnelli, CUBE alumni, Vice President of Product, Virtual CPUs at NVIDIA, Kevin Gray, Director of Product Marketing, Dell EMC, thanks for coming back on, thanks for, good to see you. Awesome, great to see you guys too. So NVIDIA, big news we saw, your CEO up on the keynote, videoing in, two big announcements, you got some stats on, some window stats to talk about, let's talk the news first, get the news out of the way. Sure, so at this show NVIDIA announced our new product called the 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, so this runs on top of vSphere, and also in conjunction with our partner Dell, so all of this Virtual Compute Server runs on Dell VxRail as well. And what's the impact on a B for them, what does that mean for the customers? So for customers it's really going to be the on-ramp for enterprise AI, so a lot of customers, let's say they have a team of maybe eight data scientists who are doing data analytics. If they want to move to a 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, and then as their models get bigger and their data gets bigger, they move to one user per GPU, and then ultimately, because we support multiple GPUs now as part of this, they move to a VM that has maybe four GPUs in it, so we allow the enterprise to start to move onto AI and deep learning, in particular, machine learning for data analytics very easily. GPUs are in high demand. I mean, my son always wants to do next to Nvidia. Pratt told me to get some GPUs from you when you came on. Yes, Nvidia got against him for his gaming rig, but that's, you know, getting aside, you're 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. So again, 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 and XGBoost to use a GPU. And so 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 at scale. So what they want to do is they want to move to the cloud so they can have hundreds or thousands of GPUs. So 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. And that's the road map. So you can get in, get the work done, scale up, that's the benefit of that. And availability timing, when all is going to hit. So virtual compute server is available on Friday the 29th and then we're looking at mid next year for the full suite of VMware cloud on top of AWS T4. Great Kevin, you guys are supplier here at Dell EMC. What's the positioning there with you guys? So we're working very closely with Nvidia in general on all their efforts around both AI as well as VDI too. So we've worked quite a bit, most recently on the VDI front as well. So we will look to, you know, drive things like qualifying the devices, there's both VDI or analytics applications. Okay Kevin, bring us up to date because you know it's funny, we were talking about, this is our 10th year here at the show. And I remember, you know, sitting across Howard Street here in 2010 and you know, 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, so I'll go ahead. I'm going to say, so one of the things that we've learned with Nvidia is that it's really about the user experience. Right, so 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. And 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. Right, that 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. So now we're focused on user experience. So in 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. But you pop a GPU in there and you're good. And most of our customers together are working on a five year life cycle. So 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 the office applications. So 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. And the auto updates are, this is the push notification in the world we live in. This has to be built in from day one. Absolutely, and if you look what Dell's doing, we've really built this into both our VX rails and our VX blocks. So GPUs are just now part of it and we do these fully qualified stacks specifically for VDI environments as well. So we're working a lot with the N-vector tools to make sure they're qualified for user experience. All these years. Yes, yes, and 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. And so we put this tool together but Dell has really been taking the lead on testing it and promoting it to the users to really drive the cost effectiveness. So it still is about the dollar per desktop but it's the dollar per dazzling desktop. All right, so 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 that's not the gaming platform they're using because I know how important that is. Absolutely, but there's a ton of customers that are out there that we're using. We look at Flux like Google Evans is an example of a company that's worked with us in NVIDIA to truly drive types of applications that are essential to VDI. And so 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 you mentioned, Stu, and you pointed out brilliantly was that VDI is not just an IT thing anymore. I mean, 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, you don't have a kick-ass rig. You can call it, right? I mean, multiple monitors. That's the expectation, and again, mobility. So work experience, workspace, that one. Exactly along those same lines, by the way. This is the whole category, and 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, right? So it's how do I get my job done? So we used to use words like business worker and knowledge worker. It's just I'm a worker. Everybody today uses their phone, it's mobile, they use their computer at home, they use their computer at work, and they're all running with dual monitors, right? So 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 and your GPU accelerated, but it's things like Skype, WebEx, Zoom, all the collaboration tool, Microsoft Teams, they all benefit from our joint solution with the GPU. These new subsystems like GPUs become so critical, they're not just subsystems, they are the main part because the offload is now part of the new operating environment. So we optimized together jointly using the Invector tool, we optimized the server and operating environment so that if you're running the GPU, you can right size your CPU in terms of cores, speed, et cetera, so that you get the best user experience and the most cost effective way. And also, you know, so the gaming world helps bring in the new kind of cool visualization. That's going to move into just the workflow of workers, right? So like, 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, right? 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 focus and get some tracing in there. Kevin, I know I've seen things from the Dell family on leveraging VR in the enterprise space. Oh, absolutely. So, I mean, 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, and those are areas that'll continue to use things like GPUs to help accelerate those types of applications. So it really does come down to having that scalable infrastructure that's easy to manage and easy to operate, and that's where I think the partnership with NVIDIA really comes together. And deep learning and all the stuff around data, I mean, Michael Dell always comes on the cube, talks about it. And he sees data as the biggest opportunity and challenge. And whatever application is coming in, you got to be able to pound that data. That's where AI is really shown. Our machine learning has kind of shown that that's helping heavy lifting a lot of things that were either manual. Exactly, so 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. So 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, right? Cause I get four more extra work days. And the other thing that's really interesting is our joint solution is you can leverage that same virtual GPU technology so 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. It's really great. Productivity gains just from an infrastructure, even the user too, I mean, up and down the productivity gains are significant. Exactly. So I get three monitors now. I'm going to get one with Alienware, you know, Curve monitors, yeah. Just the difference we had, we have a suite here at the show, and just the difference, you can see such a difference and just when you insert the GPUs into the platform, it just makes all the difference. So John, I got to ask you a personal question. How many times do people ask you for a GPU? I mean, you must get that all the time. We do, you know, I have an NVIDIA backpack, and when I walk around, you know, there's a lot of people that only know NVIDIA for gaming. So it's just, you know, random people will always ask for that. I got two suns and two doors, and they just nerd out on the GPUs. Oh, I think, I think he's trying to get me to commit on camera, to give him a GPU. I think I'm in trouble here. They got the latest and greatest. Any new stuff would be happy to be first on the block and get that, the GPU. And it certainly impact on the infrastructure side, components, the operating environment, Windows 10, any other data you guys have to share that you think is notable around, you know, how all this is coming together, working from user experience around Windows and VDI. So I think one piece of data, again, going back to your first comment about, you know, cost per desktop. So, you know, we're seeing a lot of migration to Windows 10 and customers are buying our joint solution from Dell, which includes our hardware and software, and they're buying that five year program, five year life cycle. So we actually put a program in place to really drive down the cost. So it's literally like $3 per month to have a GPU accelerated virtual desktop. So it's really great value for the customers besides the great productivity. And if you look at doing some of these workloads on-premises, some of the cost can come down. We had a recent study around the VX block as an example and we showed that running GPUs and VDI can be as much as 45% less on a VX block at scale. So, you know, when you talk about the whole hybrid cloud, multi-cloud strategy, there's pluses and minuses to both. But certainly, if we look at some of the ability to start small and scale out, whether you're going HEI or you're going CI, I think there's a VDI solution there that can really drive the economics. 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. So we just did a certification on our platforms with DeSau, Skatia system, and that's an area that we'll continue to explore as we move forward. Yeah, I think in the workstation side of things is all the standard, you know, it's automotive, it's manufacturing. Architecture is interesting. You know, architecture is one of those companies that has kind of an SMB profile, because they have lots of offices, but they have enterprise requirements for all the hard work that they do. And then with VDI, we're very strong in financial services as well as healthcare. In fact, if you haven't seen it, you should come by, we have a Bloomberg demo for financial services about the impact of for traders by having a virtualized, virtual GPU desktop. Yeah, so speed is critical for them. Final question, take away from the show this year, 2019, VMworld, Stu, we got 10 years to look back, but guys, take away 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 their migration to Windows 10, and they're coming to us saying, oh my gosh, I only have till January, what can you do to help me? Get some GPs, thoughts from the show? I just, you know, how the multicloud world continues to evolve, you know, the continued partnerships that emerge as part of this is just pretty amazing and how that's changing and things like, you know, virtual GPUs and accelerators and that experience that people come from, expect from the cloud is something that I, for me, is a takeaway. John Finnelli and Vidya, thanks for coming on. Congratulations on all the success. Thank you. Kevin, Ian, Delham C, thanks for coming on. Thank you. Appreciate it, thanks for the insights. Thanks to you. Here in theCUBE, VMworld 2019, and John Furrier with Stu Miniman, stay with us for more live coverage of this short break.