>>We're back at Supercomputing 22 in Dallas, winding down day four of this conference. I'm Paul Gillan, my co-host Dave Nicholson. We are talking, we've been talking super computing all week and you hear a lot about what's going on in the United States, what's going on in China, Japan. What we haven't talked a lot about is what's going on in Europe and did you know that two of the top five supercomputers in the world are actually from European countries? Well, our guest has a lot to do with that. Florian, bearish, I hope I pronounce that correctly. My German is, German is not. My strength is the operations director for price, ais, S B L. And let's start with that. What is price? >>So, hello and thank you for the invitation. I'm Flon and Price is a partnership for Advanced Computing in Europe. It's a non-profit association with the seat in Brussels in Belgium. And we have 24 members. These are representatives from different European countries dealing with high performance computing in at their place. And we, so far, we provided the resources for our European research communities. But this changed in the last year, this oral HPC joint undertaking who put a lot of funding in high performance computing and co-funded five PET scale and three preis scale systems. And two of the preis scale systems. You mentioned already, this is Lumi and Finland and Leonardo in Bologna in Italy were in the place for and three and four at the top 500 at least. >>So why is it important that Europe be in the top list of supercomputer makers? >>I think Europe needs to keep pace with the rest of the world. And simulation science is a key technology for the society. And we saw this very recently with a pandemic, with a covid. We were able to help the research communities to find very quickly vaccines and to understand how the virus spread around the world. And all this knowledge is important to serve the society. Or another example is climate change. Yeah. With these new systems, we will be able to predict more precise the changes in the future. So the more compute power you have, the better the smaller the grid and there is resolution you can choose and the lower the error will be for the future. So these are, I think with these systems, the big or challenges we face can be addressed. This is the climate change, energy, food supply, security. >>Who are your members? Do they come from businesses? Do they come from research, from government? All of the >>Above. Yeah. Our, our members are public organization, universities, research centers, compute sites as a data centers, but But public institutions. Yeah. And we provide this services for free via peer review process with excellence as the most important criteria to the research community for free. >>So 40 years ago when, when the idea of an eu, and maybe I'm getting the dates a little bit wrong, when it was just an idea and the idea of a common currency. Yes. Reducing friction between, between borders to create a trading zone. Yes. There was a lot of focus there. Fast forward to today, would you say that these efforts in supercomputing, would they be possible if there were not an EU super structure? >>No, I would say this would not be possible in this extent. I think when though, but though European initiatives are, are needed and the European Commission is supporting these initiatives very well. And before praise, for instance 2008, there were research centers and data centers operating high performance computing systems, but they were not talking to each other. So it was isolated praise created community of operation sites and it facilitated the exchange between them and also enabled to align investments and to, to get the most out of the available funding. And also at this time, and still today for one single country in Europe, it's very hard to provide all the different architectures needed for all the different kind of research communities and applications. If you want to, to offer always the latest technologies, though this is really hardly possible. So with this joint action and opening the resources for other research groups from other countries, you, we, we were able to, yeah, get access to the latest technology for different communities at any given time though. And >>So, so the fact that the two systems that you mentioned are physically located in Finland and in Italy, if you were to walk into one of those facilities and meet the people that are there, they're not just fins in Finland and Italians in Italy. Yeah. This is, this is very much a European effort. So this, this is true. So, so in this, in that sense, the geography is sort of abstracted. Yeah. And the issues of sovereignty that make might take place in in the private sector don't exist or are there, are there issues with, can any, what are the requirements for a researcher to have access to a system in Finland versus a system in Italy? If you've got a EU passport, Hmm. Are you good to go? >>I think you are good to go though. But EU passport, it's now it becomes complicated and political. It's, it's very much, if we talk about the recent systems, well first, let me start a praise. Praise was inclusive and there was no any constraints as even we had users from US, Australia, we wanted just to support excellence in science. And we did not look at the nationality of the organization, of the PI and and so on. There were quotas, but these quotas were very generously interpreted. So, and if so, now with our HPC joint undertaking, it's a question from what European funds, these systems were procured and if a country or being country are associated to this funding, the researchers also have access to these systems. And this addresses basically UK and and Switzerland, which are not in the European Union, but they were as created to the Horizon 2020 research framework. And though they could can access the systems now available, Lumi and Leono and the Petascale system as well. How this will develop in the future, I don't know. It depends to which research framework they will be associated or not. >>What are the outputs of your work at price? Are they reference designs? Is it actual semiconductor hardware? Is it the research? What do you produce? >>So the, the application we run or the simulation we run cover all different scientific domains. So it's, it's science, it's, but also we have industrial let projects with more application oriented targets. Aerodynamics for instance, for cars or planes or something like this. But also fundamental science like the physical elementary physics particles for instance or climate change, biology, drug design, protein costa, all these >>Things. Can businesses be involved in what you do? Can they purchase your, your research? Do they contribute to their, I'm sure, I'm sure there are many technology firms in Europe that would like to be involved. >>So this involving industry though our calls are open and is, if they want to do open r and d, they are invited to submit also proposals. They will be evaluated and if this is qualifying, they will get the access and they can do their jobs and simulations. It's a little bit more tricky if it's in production, if they use these resources for their business and do not publish the results. They are some, well, probably more sites who, who are able to deal with these requests. Some are more dominant than others, but this is on a smaller scale, definitely. Yeah. >>What does the future hold? Are you planning to, are there other countries who will be joining the effort, other institutions? Do you plan to expand your, your scope >>Well, or I think or HPC joint undertaking with 36 member states is quite, covers already even more than Europe. And yeah, clearly if, if there are other states interest interested to join that there is no limitation. Although the focus lies on European area and on union. >>When, when you interact with colleagues from North America, do you, do you feel that there is a sort of European flavor to supercomputing that is different or are we so globally entwined? No. >>So research is not national, it's not European, it's international. This is also clearly very clear and I can, so we have a longstanding collaboration with our US colleagues and also with Chap and South Africa and Canada. And when Covid hit the world, we were able within two weeks to establish regular seminars inviting US and European colleagues to talk to to other, to each other and exchange the results and find new collaboration and to boost the research activities. So, and I have other examples as well. So when we, we already did the joint calls US exceed and in Europe praise and it was a very interesting experience. So we received applications from different communities and we decided that we will review this on our side, on European, with European experts and US did it in US with their experts. And you can guess what the result was at the meeting when we compared our results, it was matching one by one. It was exactly the same. Recite >>That it, it's, it's refreshing to hear a story of global collaboration. Yeah. Where people are getting along and making meaningful progress. >>I have to mention you, I have to to point out, you did not mention China as a country you were collaborating with. Is that by, is that intentional? >>Well, with China, definitely we have less links and collaborations also. It's also existing. There, there was initiative to look at the development of the technologies and the group meet on a regular basis. And there, there also Chinese colleagues involved. It's on a lower level, >>Yes, but is is the con conversations are occurring. We're out of time. Florian be operations director of price, European Super Computing collaborative. Thank you so much for being with us. I'm always impressed when people come on the cube and submit to an interview in a language that is not their first language. Yeah, >>Absolutely. >>Brave to do that. Yeah. Thank you. You're welcome. Thank you. We'll be right back after this break from Supercomputing 22 in Dallas.

>> Announcer: theCUBE presents HPE Discover 2022. Brought to you by HPE. >> Okay, we're back here at HPE Discover 2022, theCUBE's continuous coverage. This is day two, Dave Vellante with John Furrier. John Frey's here. He is the chief technologist for sustainable transformation at Hewlett Packard Enterprise and Justin Murrill who's the director of corporate responsibility for AMD. Guys, welcome to theCUBE. Good to see you. >> Thank you. >> Thank you. It's great to be here. >> So again, I remember the days where, you know, CIOs didn't really care about the power budget. They didn't pay the power budget. You had, you know, facilities over here, IT over here and they didn't talk to each other. That's changed. Why is there so much discussion around sustainable IT today? >> It's exciting to see how much it's up leveled, as you say. I think there are a couple different trends happening but mainly, you know, the IT teams and IT leaders that are making decisions are seeing to your point how their decisions are affecting enterprise level, greenhouse gas emission reduction goals. So that connection is becoming very clear. Everything from the server processor to beyond it, those decisions have a key role. And importantly we're seeing, you know, 60% of the Fortune 500 now have climate or energy efficiency related goals. So there's a perfect storm of sorts happening where more companies setting goals, IT decision makers looking particularly at the data center because as the computational heart of an organization, it has a wealth of opportunity from an energy and a mission savings perspective. >> I'm surprised it's only 60%. I mean, that number really shocked me. So it's got to be a 100% within the next couple of years here. I would think, I mean, it's not trivial, right? You've got responsibilities in terms of reporting and you can't just mail it in, right? >> Yeah, absolutely. So there's a lot more disclosure happening but the goal setting is really upleveling as well. >> And the metrics involved too. Can you just scope the scale and challenge of like getting the right metrics, not when you have the goals. Does that factor in, how do you see there? What's your commentary on that? >> Yeah, I think there's, the aperture is continuing to open as metrics go, so to speak. So from an operations perspective, companies are reporting on what's referred to as scope one and scope two. And scope two is the big one from electricity, right? And then scope three is everything else. That's the supply chain and the outside of that. So a lot of implications there as well from IT decision making. >> Is there a business case for sustainable IT? I mean, you're probably not going to lower the power budget, right? But is it just, hey, it's the right thing to do. We have to do it, it's good for the brand. It'll allow us to attract people or is there a a more of a rich business case? >> So there really is a business case even just within inside the data center walls, for example. There's inefficiencies that are inherent in many of these data centers. There's really low utilization levels as well. And by reducing over provisioning and increasing utilization, there's real money to be saved in terms of equipment costs, maintenance agreement costs, software licensing costs. So actually the power consumption and the environmental piece is an added benefit but it's not the main reason. So we actually had IDC do a survey for us last year and we asked IT executives, 500 senior IT executives, were you implementing sustainable IT programs and why? My guess initially was about 40% of them would say yes. Actually the number was 96% of them. And when we asked them why they fell into three categories. The digital leaders, those that are the early adopters moving the quickest. They said we do it to attract and retain institutional investors. They've been hearing from their boards. They've been hearing from their investor relations teams and investors are starting to ask and even in a couple cases board seats are becoming contentious based on the environmental perspective of the person being nominated. This digital mainstream, the folks in the middle about 80% of the total pie, they're doing it to attract and retain customers because customers are asking them about their sustainable IT programs. If they're a non-manufacturing customer, their data center consumption is probably the largest part of their company. It's also by the way usually the most expensive real estate the company owns. So customers are asking and customers are not only asking, do you have basic programs in place? But they're asking, what are your goals to Justin's point? The customers are starting to realize that carbon goals have been vaguely defined historically. So they're asking for specificity, they're asking for transparency and by the way the science-based target initiative recently released their requirements for net zero science-based targets. And that requires significant reduction to your point before you start considering renewable energy in that balance. The third reason those digital followers, that slowest group or folks that are in industries that move the slowest, they said they were doing this to attract and retain employees. Because they recognize the data scientists, the computer science, computer engineering students that they're trying to attract want to work at a company where they can see how what they do directly contributes to purpose. And they vote with their feet. If they come on and they can't make that connection pretty quickly or if they spend a lot of their time chasing down inefficiencies in a technology infrastructure, they're not going to stay there very long. >> I mean, the mission-driven organization is definitely an employee factor. People are interested in that. The work for company is responsible, doing the right thing but that business case is interesting because I think there's recognition now more than ever before. You think you're right on. It used to be kind of like mailed it in before. Okay, we're doing some stuff. Now it's like, we all have to do it. And it's a board issue. It's a financing issue. It might be a filing issue as you guys mentioned. So that's all great. So I got to ask how you guys specifically are working together, AMD and HPE. What are you guys doing to make it more efficient? And then I'll see with Cloud and Cloud scale, there's more servers being shipped now than ever before. And more devices at the edge. What are you guys doing together specifically? >> Yeah, we've been working together, AMD and HPE on advancing sustainability for many years. I've had the opportunity to working directly with John for many years and I've learned a lot from him and your team. It's fantastic to see all the developments here. I mean, so most recently the top 500 and the green 500 list of supercomputers came out. And at the top of that list is AMD HPE systems. And it shows kind of the pinnacle of what can be possible for other data centers looking to modernize and scale. So the number one system, the fastest system in the world and the most energy efficient system in the world, the Frontier supercomputer has AMD HPE technology in it. And it just passed the exit scale barrier. I mean, I'm still just blown away by this. A billion, billion calculations per second. It's just amazing. And the research is doing around clean energy, alternative energy sources, scientific research is really exciting. So there's that. The other system that really jumps out is the LUMI system, the number three system because it's a 100% powered by renewable energy. So not only that, it takes the heat and it channels it to a nearby town and covers 20% of that town's heating needs thereby avoiding 12,400 metric tons of carbon emissions. So this system is carbon negative, right? And you just go down the list. I mean, AMD is in the top eight out of 10 most green... >> Rewind that second. So you have the heat and the power shifting to a town? >> Yes, the LUMI supercomputer has the heat from the system to an nearby town. It's like a closed loop, the idea of circular economy but with energy. And it takes that waste and it makes it an input, a resource. >> But this is the kind of innovation that's going on, right? This is the scale, this is where scale and efficiency kind of come together. That's huge. Where's that going to go? What's your perspective on where that goes next because that's a blueprint that could be replicated. >> You bet. So I think we're going to continue to see overall power consumption go up at the system level. But performance per wat is climbing much more dramatically. So I think that's going to continue to scale. It's going to require a new cooling technology. So direct liquid cooling is becoming more and more in use and customers really interested in that. There's shifting from industry standard architectures to lower end high performance computer architectures to get direct liquid cooling, higher core processors and get the performance they want in a smaller footprint. And at the same time, they're really thinking about how do we operate the infrastructure as a system not as individual piece parts. And one of the things that Frontier and LUMI do so well is they were designed from the start as a system, not as piece parts making up the system. So I think that happens. The other thing that's really critical is no one company is going to solve these challenges ourself. So one of the things I love about our partnership with AMD is we look at each other's sustainability goals before we launch 'em. We say, well, how can we help? One of AMD's goals that I'll let Justin talk about came about because HPE at the time of separation laid a really aggressive product, energy efficiency goal out, said but we're not sure how we're going to make this. And AMD said we can help. So that collaboration, we critique each other's programs, we push each other, but we work together. I like to say partnership is leadership in this. >> Well, that's a nuance point. Before you get to that solution there Justin, this system's thinking is really important. You're seeing that now with Cloud. Some of the things that GreenLake and the systems are pointing out, this holistic systems' thinking is applied to partnerships, not just the company. >> Yep. >> This is a really nuanced point but we're seeing that more and more. >> Yeah, absolutely. In fact, Justin mentioned the heat reuse, same way with the national renewable energy lab. They actually did snow removal and building heating with the heat reuse. So if you're designing for example, a liquid cold system from the start, how do you make it a symbiotic relationship? There's more and more interest in co-locating data centers and greenhouses in colder environments for example. Because the principle of the circular economy is nothing is waste. So if you think it's waste or you think it's a byproduct, think about how can that be an input to something else. >> Right, so you might put a data center so you can use ambient cooling or in somewhere in the Columbia River so you can, you know, take advantage of, you know, renewable energy. What are some goals that you guys can share with us? >> So we've got some great momentum and a track record coming off of, going back to 2014, we set a 25 by 20 goal to improve the energy efficiency for our mobile processors and mobile devices, right? So laptops. And we were able to achieve a 31.7x in that timeframe. So which was twice the industry trend to that. And then moving on, we've doubled down on data center and we've set a new goal of a 30x increase in energy efficiency for our server processors and accelerators to really focused on HPC and AI training. So that's a 30x goal over 2020 to 2025 focused on these really important workloads 'cause they're fast growing. We heard yesterday 150 billion devices connected by 2025 generating a lot of data, right? So that's one of the reasons why we focused on that. 'Cause these are demanding workloads. And this represents a 2.5x increase over the historical trend, right? And fundamentally speaking, that's a 97% reduction in energy use per computation in five years. So we're very pleased. We announced an update recently. We're at 6.8x. We're on track for this goal and making great progress and showing how these, you know, solutions at a processor level and an accelerator level can be amplified, taken into HPE technology. >> Generally tech companies, you know, that compete want to rip each other's faces off. And is that the case in this space or do you guys collaborate with your competitors to share best practice? Is that beginning? Is it already there? >> There's much more collaboration in this space. This is one of the safe places I think where collaboration does occur more. >> Yeah. And we've all got to work together. A great example that was in the supply chain. When HPE first set our supply chain expectations for our suppliers around things like worker rights and environment and worker protection from a health and safety perspective. We initially had our code of conduct asked their suppliers to comply with it. Started auditing in event. And we quickly got into the factories and saw they were doing it for our workloads. But if you looked around the factory, they weren't doing in other places. And we took a step back and said, well, wait a minute. Why is that? And they said that vendor doesn't require it. So we took a step back and said let's get the industry together. We share a common supply chain. How do we have a common set of expectations and push them out to our supply chain? How to now do third party audits so the same supplier doesn't get audited by each of the major vendors and then share those audit results. And what we found was that really had a large lever effect of moving the electronic supply chain much more rapidly towards our expectations in all those areas. Well then other industries looked and said, well, wait a minute, if that worked for electronics, it'll probably work broader. And so now, the output of that is what's called the responsible business alliance across many industries taking that same approach. So that's a pre-competitive. We all have the same challenge. In many cases we share a common supply chain. So that's a great example of electronic companies coming together, design standards for things. There's a green grid group at the moment looking at liquid cooling connects. You know, we don't want every vendor to have a different connection point for liquid cooling for example. So how do we standardize that to make our customers have a easier time about looking at the technologies they want from any vendor and having common connection points. >> Right. Okay. So a lot of collaboration. Last question. How much of a difference do you think it can make? In other words, what percent of the blame pie goes to information technology? And I think regardless, you got to do your part. Will it make a dent? >> I think the sector has done a really good job of keeping that increase from going up while exponentially increasing performance. So it's been a really amazing industry effort. And moving forward, I think this is more important than ever, right? And with the slowdown of Moore's law we're seeing more gains that need to come from beyond process architecture to include packaging innovations, to power management, to just the architecture here. So the challenge of mitigating and minimizing energy growth is important. And we believe like with that 30x energy efficiency goal that it is doable but it does take a lot of collaboration and focus. >> That's a great point. I mean, if you didn't pay attention to this, IT could really become a big piece of the pie. Guys thanks so much for coming on theCUBE. Really appreciate. >> People are watching. They're paying attention at all levels. Congratulations. >> Absolutely. >> All right, Dave Vellante, John Furrier and our guests. Don't forget to go to SiliconANGLE.com for all the news. Our YouTube channel, actually go to CUBE.net. You'll get all these videos in our YouTube channel, youtube.com/SiliconANGLE. You can check out everything on demand. Keep it right there. We'll be right back. HPE Discover 2022 from Las Vegas. You're watching theCUBE. (soft music)

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's coverage of HPE. Discover 22 live from the Sans expo center in Las Vegas. Lisa Martin, here with Dave Velante. We've an alumni back joining us to talk about high performance computing and AI, Justin ARD, EVP, and general manager of HPC and AI at HPE. That's a mouthful. Welcome back. >>It is no, it's great to be back and wow, it's great to be back in person as well. >>It's it's life changing to be back in person. The keynote this morning was great. The Dave was saying the energy that he's seen is probably the most out of, of any discover that you've been at and we've been feeling that and it's only day one. >>Yeah, I, I, I agree. And I think it's a Testament to the places in the market that we're leading the innovation we're driving. I mean, obviously the leadership in HPE GreenLake and, and enabling as a service for, for every customer, not just those in the public cloud, providing that, that capability. And then obviously what we're doing at HPC and AI breaking, uh, you know, breaking records and, uh, advancing the industry. So >>I just saw the Q2 numbers, nice revenue growth there for HPC and AI. Talk to us about the lay of the land what's going on, what are customers excited about? >>Yeah. You know, it's, it's a, it's a really fascinating time in this, in this business because we're, you know, we just, we just delivered the first, the world's first exo scale system. Right. And that's, uh, you know, that's a huge milestone for our industry, a breakthrough, you know, 13 years ago, we did the first Petta scale system. Now we're doing the first exo scale system, huge advance forward. But what's exciting too, is these systems are enabling new applications, new workloads, breakthroughs in AI, the beginning of being able to do proper quantum simulations, which will lead us to a much, you know, brighter future with quantum and then actually better and more granular models, which have the ability to really change the world. >>I was telling Lisa that during the pandemic we did, uh, exo scale day, it was like this co yep. You know, produce event. And we weren't quite at exo scale yet, but we could see it coming. And so it was great to see in frontier and, and the keynote you guys broke through that, is that a natural evolution of HPC or is this we entering a new era? >>Yeah, I, I think it's a new era and I think it's a new era for a few reasons because that, that breakthrough really, it starts to enable a different class of use cases. And it's combined with the fact that I think, you know, you look at where the rest of the enterprises data set has gone, right? We've got a lot more data, a lot more visibility to data. Um, but we don't know how to use it. And now with this computing power, we can start to create new insights and new applications. And so I think this is gonna be a path to making HPC more broadly available. And of course it introduces AI models at scale. And that's, that's really critical cause AI is a buzzword. I mean, lots of people say they're doing AI, but when you know, to, to build true intelligence, not, not effectively, you know, a machine that learns data and then can only handle that data, but to build true intelligence where you've got something that can continue to learn and understand and grow and evolve, you need this class of system. And so I think we're at, we're at the forefront of a lot of exciting innovation. H how, >>In terms of innovation, how important is it that you're able to combine as a service and HPC? Uh, what does that mean for, for customers for experimentation and innovation? >>You know, a couple things I've been, I've actually been talking to customers about that over the last day and a half. And, you know, one is, um, you think about these, these systems are, they're very large and, and they're, they're pretty, you know, pretty big bets if you're a customer. So getting early access to them right, is, is really key, making sure that they're, they can migrate their software, their applications, again, in our space, most of our applications are custom built, whether you're a, you know, a government or a private sector company, that's using these systems, you're, you're doing these are pretty specialized. So getting that early access is important. And then actually what we're seeing is, uh, with the growth and explosion of insight that we can enable. And some of the diversity of, you know, new, um, accelerator partners and new processors that are on the market is actually the attraction of diversity. And so making things available where customers can use multimodal systems. And we've seen that in this era, like our customer Lumi and Finland number, the number three fastest system in the world actually has two sides to their system. So there's a compute side, dense compute side and a dense accelerator side. >>So Oak Ridge national labs was on stage with Antonio this morning, the, the talking about frontier, the frontier system, I thought what a great name, very apropo, but it was also just named the number one to the super computing, top 500. That's a pretty big accomplishment. Talk about the impact of what that really means. >>Yeah. I, I think a couple things, first of all, uh, anytime you have this breakthrough of number one, you see a massive acceleration of applications. And if you really, if you look at the applications that were built, because when the us department of energy funded these Exoscale products or platforms, they also funded app a set of applications. And so it's the ability to get more accurate earth models for long term climate science. It's the ability to model the electrical grid and understand better how to build resiliency into that grid. His ability is, um, Dr. Te Rossi talked about a progressing, you know, cancer research and cancer breakthroughs. I mean, there's so many benefits to the world that we can bring with these systems. That's one element. The other big part of this breakthrough is actually a list, a lesser known list from the top 500 called the green 500. >>And that's where we measure performance over power consumption. And what's a huge breakthrough in this system. Is that not only to frontier debut at number one on the top 500, it's actually got the top two spots, uh, because it's got a small test system that also is up there, but it's got the top two spots on the green 500 and that's actually a real huge breakthrough because now we're doing a ton more computation at far lesser power. And that's really important cuz you think about these systems, ultimately you can, you can't, you know, continue to consume power linearly with scaling up performance. There's I mean, there's a huge issue on our impact on our environment, but it's the impact to the power grid. It's the impact to heat dissipation. There's a lot of complexities. So this breakthrough with frontier also enables us no pun intended to really accelerate, you know, the, the capacity and scale of these systems and what we can deliver. >>It feels like we're entering a new Renaissance of HPC. I mean, I'm old enough to remember. I, it was, it wasn't until recently my wife, not recently, maybe five, six years ago, my wife threw out my, my green thinking machines. T-shirt that Danny Hillis gave you guys probably both too young to remember, but you had thinking machines, Ken to square research convex tried to mini build a mini computer HPC. Okay. And there was a lot of innovation going on around that time and then it just became too expensive and, and, and other things X 86 happened. And, and, but it feels like now we're entering a, a new era of, of HPC. Is that valid or is it true? What's that mean for HPC as an industry and for industry? >>Yeah, I think, I think it's a BR I think it's a breadth. Um, it's a market that's opening and getting much more broader the number of applications you can run, you know, and we've traditionally had, you know, scientific applications, obviously there's a ton in energy and, and you know, physics and some of the traditional areas that obviously the department of energy sponsor, but, you know, we saw this with, with even the COVID pandemic, right? Our, our supercomputers were used to identify the spike protein to, to help and validate and test these vaccines and bring them to market and record time. We saw some of the benefits of these breakthroughs. And I think it's this combination of that, that we actually have the data, you know, it's, it's digital, it's captured, um, we're capturing it at, you know, at the edge, we're capturing it and, and storing it obviously more broadly. So we have the access to the data and now we have the compute power to run it. And the other big thing is the techniques around artificial intelligence. I mean, what we're able to do with neural networks, computer vision, large language models, natural language processing. These are breakthroughs that, um, one require these large systems, but two, as you give them a large systems, you can actually really enable acceleration of how sophisticated these, these applications can get. >>Let's talk about the impact of the convergence of HPC and AI. What are some of the things that you're seeing now and what are some of the things that we're gonna see? >>Yeah. So, so I, one thing I like to talk about is it's, it's really, it's not a convergence. I think it's it. Sometimes it gets a little bit oversimplified. It's actually, it's traditional modeling and simulation leveraging machine learning to, to refine the simulation. And this is a, is one of the things we talk about a lot in AI, right? It's using machine learning to actually create code in real time, rather than humans doing it, that ability to refine the model as you're running. So we have an example. We did a, uh, we, we actually launched an open source solution called smart SIM. And the first application of that was climate science. And it's what it's doing is it's actually learning the data from the model as the simulation is running to provide more accurate climate prediction. But you think about that, that could be run for, you know, anything that has a complex model. >>You could run that for financial modeling, you can use AI. And so we're seeing things like that. And I think we'll continue to see that the other side of that is using modeling and simulation to actually represent what you see in AI. So we were talking about the grid. This is one of the Exoscale compute projects you could actually use once you actually get, get the data and you can start modeling the behavior of every electrical endpoint in a city. You know, the, the meter in your house, the substation, the, the transformers, you can start measuring the FX of that. You can then build equations. Well, once you build those equations, you can then take a model, cuz you've learned what actually happens in the real world, build the equation. And then you can provide that to someone who doesn't need a extra scale supercomputer to run it, but that, you know, your local energy company can better understand what's happening and they'll know, oh, there's a problem here. We need to shift the grid or respond more, more dynamically. And hopefully that avoids brownouts or, you know, some of the catastrophic outages we've >>Seen so they can deploy that model, which, which inherently has that intelligence on sort of more cost effective systems and then apply it to a much broader range. Do any of those, um, smart simulations on, on climate suggest that it's, it's all a hoax. You don't have to answer that question. <laugh> um, what, uh, >>The temperature outside Dave might, might give you a little bit of an argument to that. >>Tell us about quantum, what's your point of view there? Is it becoming more stable? What's H HPE doing there? >>Yeah. So, so look, I think there's, there's two things to understand with quantum there's quantum hardware, right? Fundamentally, um, how, um, how that runs very differently than, than how we run traditional computers. And then there's the applications. And ultimately a quantum application on quantum hardware will be far more efficient in the future than, than anything else. We, we see the opportunity for, uh, much like we see with, you know, with HPC and AI, we just talked about for quantum to be complimentary. It runs really well with certain applications that fabricate themselves as quantum problems and some great examples are, you know, the, the life sciences, obviously quantum chemistry, uh, you see some, actually some opportunities in, in, uh, in AI and in other areas where, uh, quantum has a very, very, it, it just lends itself more naturally to the behavior of the problem. And what we believe is that in the short term, we can actually model quantum effectively on these, on these super computers, because there's not a perfect quantum hardware replacement over time. You know, we would anticipate that will evolve and we'll see quantum accelerators much. Like we see, you know, AI accelerators today in this space. So we think it's gonna be a natural evolution in progression, but there's certain applications that are just gonna be solved better by quantum. And that's the, that's the future we'll we'll run into. And >>You're suggesting if I understood it correctly, you can start building those applications and, and at least modeling what those applications look like today with today's technology. That's interesting because I mean, I, I think it's something rudimentary compared to quantum as flash storage, right? When you got rid of the spinning disc, it changed the way in which people thought about writing applications. So if I understand it, new applications that can take advantage of quantum are gonna change the way in which developers write, not one or a zero it's one and virtually infinite <laugh> combinations. >>Yeah. And I actually, I think that's, what's compelling about the opportunity is that you can, if you think about a lot of traditional the traditional computing industry, you always had to kind of wait for the hardware to be there, to really write, write, and test the application. And we, you know, we even see that with our customers and HPC and, and AI, right? They, they build a model and then they, they actually have to optimize it across the hardware once they deploy it at scale. And with quantum what's interesting is you can actually, uh, you can actually model and, and, and make progress on the software. And then, and then as the hardware becomes available, optimize it. And that's, you know, that's why we see this. We talk about this concept of quantum accelerators as, as really interesting, >>What are the customer conversations these days as there's been so much evolution in HPC and AI and the technology so much change in the world in the last couple of years, is it elevating up the CS stack in terms of your conversations with customers wanting to become familiar with Exoscale computing? For example? >>Yeah. I, I think two things, uh, one, one is we see a real rise in digital sovereignty and Exoscale and HPC as a core fund, you know, fundamental foundation. So you see what, um, you know, what Europe is doing with the, the, the Euro HPC initiative, as one example, you know, we see the same kind of leadership coming out of the UK with the system. We deployed with them in Archer two, you know, we've got many customers across the globe deploying next generation weather forecasting systems, but everybody feels, they, they understand the foundation of having a strong supercomputing and HPC capability and competence and not just the hardware, the software development, the scientific research, the, the computational scientists to enable them to remain competitive economically. It's important for defense purposes. It's important for, you know, for helping their citizens, right. And providing, you know, providing services and, and betterment. >>So that's one, I'd say that's one big theme. The other one is something Dave touched on before around, you know, as a service and why we think HP GreenLake will be, uh, a beautiful marriage with our, with our HPC and AI systems over time, which is customers also, um, are going to scale up and build really complex models. And then they'll simplify them and deploy them in other places. And so there's a number of examples. We see them, you know, we see them in places like oil and gas. We see them in manufacturing where I've gotta build a really complex model, figure out what it looks like. Then I can reduce it to a, you know, to a, uh, certain equation or application that I can then deploy. So I understand what's happening and running because you, of course, as much as I would love it, you're not gonna have, uh, every enterprise around the world or every endpoint have an exit scale system. Right. So, so that ability to, to, to really provide an as a service element with HP GreenLake, we think is really compelling. >>HP's move into HPC, the acquisitions you've made it really have become a differentiator for the company. Hasn't it? >>Yeah. And I, and I think what's unique about us today. If you look at the landscape is we're, we're really the only system provider globally. Yeah. You know, there are, there are local players that we compete with. Um, but we are the one true global system provider. And we're also the only, I would say the only holistic innovator at the system level to, to, you know, to credit my team on the work they're doing. But, you know, we're, we're also very committed to open standards. We're investing in, um, you know, in a number of places where we contribute the dev the software assets to open source, we're doing work with standards bodies to progress and accelerate the industry and enable the ecosystem. And, uh, and I think that, you know, ultimately the, the, the last thing I'd say is we, we are so connected in, um, with, through our, through the legacy or the, the legend of H Hewlett Packard labs, which now also reports into me that we have these really tight ties into advanced research and that some of that advanced research, which isn't just, um, around kind of core processing Silicon is really critical to enabling better applications, better use cases and accelerating the outcomes we see in these systems going forward. >>Can >>You double click on that? I, I, I wasn't aware that kind of reported into your group. Yeah. So, you know, the roots of HP are invent, right? Yeah. HP labs are, are renowned. It kinda lost that formula for a while. And now it's sounds like it's coming back. What, what, what are some of the cool things that you guys are working on? Well, >>You know, let me, let me start with a little bit of recent history. So we just talked about the exo scale program. I mean, that was a, that's a great example of where we had a public private partnership with the department of energy and it, and it wasn't just that we, um, you know, we built a system and delivered it, but if you go back a decade ago, or five years ago, there were, there were innovations that were built, you know, to accelerate that system. One is our Slingshot fabric as an example, which is a core enable of, of acceler, you know, of, of this accelerated computing environment, but others in software applications and services that allowed us to, you know, to really deliver a, a complete solution into the market. Um, today we're looking at things around trustworthy and ethical AI, so trustworthy AI in the sense that, you know, the models are accurate, you know, and that's, that's a challenge on two dimensions, cuz one is the, model's only as good as the data it's studying. >>So you need to validate that the data's accurate and then you need to really study how, you know, how do I make sure that even if the data is accurate, I've got a model that then, you know, is gonna predict the right things and not call a, a dog, a cat, or a, you know, a, a cat, a mouse or whatever that is. But so that's important. And, uh, so that's one area. The other is future system architectures because, um, as we've talked about before, Dave, you have this constant tension between the fabric, uh, you know, the interconnect, the compute and the, and the storage and, you know, constant, constantly balancing it. And so we're really looking at that, how do we do more, you know, shared memory access? How do we, you know, how do we do more direct rights? Like, you know, looking at some future system architectures and thinking about that. And we, you know, we think that's really, really critical in this part of the business because these heterogeneous systems, and not saying I'm gonna have one monolithic application, but I'm gonna have applications that need to take advantage of different code, different technologies at different times. And being able to move that seamlessly across the architecture, uh, we think is gonna be the, you know, a part of the, the hallmark of the Exoscale era, including >>Edge, which is a completely different animal. I think that's where some disruption is gonna gonna bubble up here in the next decade. >>So, yeah know, and, and that's, you know, that's the last thing I'd say is, is we look at AI at scale, which is another core part of the business that can run on these large clusters. That means getting all the way down to the edge and doing inference at scale, right. And, and inference at scale is, you know, I, I was, um, about a month ago, I was at the world economic forum. We were talking about the space economy and it's a great, you know, to me, it's the perfect example of inference, because if you get a set of data that you know, is, is out at Mars, it doesn't matter whether, you know, whether you wanna push all that data back to, uh, to earth for processing or not. You don't really have a choice, cuz it's just gonna take too long. >>Don't have that time. Justin, thank you so much for spending some of your time with Dave and me talking about what's going on with HBC and AI. The frontier just seems endless and very exciting. We appreciate your time on your insights. >>Great. Thanks so much. Thanks. >>Yes. And don't call a dog, a cat that I thought I learned from you. A dog at no, Nope. <laugh> Nope. <laugh> for Justin and Dave ante. I'm Lisa Martin. You're watching the Cube's coverage of day one from HPE. Discover 22. The cube is, guess what? The leader, the leader in live tech coverage will be right back with our next guest.

(upbeat electronic music) >> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Hi everyone, welcome back to theCUBE, we're live in Las Vegas for AWS Amazon Web Services re:Invent 2018. It's the sixth year of theCUBE coverage. Two sets wall-to-wall. Day two of day four, day one of our broadcast, two more days, wall-to-wall coverage. I'm John Furrier, your host. Our next two guests are from Druva. We've got Jaspreet Singh, CUBE alumni, founder and CEO, and Mike Palmer, chief product officer from Druva. You guys are in the middle of it, welcome to theCUBE. >> Thanks very much. >> Thanks for coming on. >> Thank you. >> Good to see you guys. I want to get into it because I just had another guest on earlier. We talked about the holy trinity of infrastructure has been compute, networking, and storage, right? Those things are not, those are evolving, now they're coming together and they're changing. You get a lot of compute here, you can do more storage there, you got networking. We're expecting to hear a lot of announcements about connectivity. But the new dynamics of the infrastructure really encapsulates why cloud's been so successful. Okay great, cloud's great, DevOps, microservices. Check check check. We all love that, we believe it. But the big thing that people, I won't say be blindsided by, but aren't talking as much about is just the impact of data. Okay, you guys were out early on it, you saw the architecture in the cloud. Are people finally getting it? The cloud and data are coming together architecturally, thinking-wise, impact to customer. You guys started attacking that problem early on. What's your vibe here at re:Invent about the role of data and cloudification? >> Sure, I think if you look back and understand why cloud happened in the first place, right? So if you look at Amazon itself or AWS, it's Amazon's retail API is applied to everything IP. Where you could, we could buy and consume services on a price point across the globe as APIs. And now if you fast-forward, the right decide the compute, network is all coming together, the new realm of self serverless computing, all these turns are pioneering more and more increased data creation. Either in the data center, at the edge, or in the cloud. And unless you do something more holistic, sort of manage it, to protect it, to manage it, it's getting harder and harder to put your arms around the data growth. And cloud is a great answer to the whole data management, or the whole creation and management of data, given that the traditional systems are not very, very defined in the way data is going. Data used to be in Oracle, and VMware, and Siebel Systems, and everything else, now it's more image sensor, media text, apps which have been created. The new realm of data is very hard to put arms around with traditional routes of putting in the box in the middle of data. That's why the cloud is key to it. >> On the product side, you guys have been attacking the data. Amazon's expecting to announce here, they've done some pre-announcements, the role of consistency. It's something that we've talked about on theCUBE in our studio and at events. You guys have been on this from day one. Cloud operations on-premises, and the cloud should look the same, has to be consistent. Andy Jassy is going to be banging that drum tomorrow in his keynote. You guys have been part of AWS for a long time, your relationship. Are they getting that messaging from you guys? (chuckles) I mean, Andy, they all be in the public cloud now that he's back on-premise. So he's listening to the customers. I mean, Andy's very straight up about it. He's like, hey, I'm a big guy. I can handle the criticism. Customers want it on-premise. I'd love her when it come to the cloud, but that's what they want. >> It certainly would be flattery that they took messaging from Druva. (John laughing) And I'm not sure that-- >> But you guys have been, cover the relationship with Amazon first. How long have you guys been working with Amazon? >> We work five years now. Very good relationship with Amazon. >> And the product side is impacted in their ecosystem. How are you guys doing relative to the architecture of Amazon? >> I think we're the only natively architected solution in the market today. And so, if you saw this morning, we were right there on the board with some of the companies that have been around for decades, primarily because if you think about the generations of data protection solutions where you started with tape on mainframe, and you moved to one of the four legacy providers in the client's server space, you had another one that really popped up with VMware. Druva really owns the cloud space. And that requires, as you mentioned, a different architecture, adoption of more of an object storage model, the ability to natively store data in a file system in the cloud. That's different than what anyone has built in the past, and I think that's what the relationship with AWS is built on. >> So you think that Jassy's going on his on-premise mess-ee-mah consistently validates what you guys do? >> Without a doubt. He's gotten a lot of customers moving to AWS over the years, and some of them have some real barriers. I think AWS is doing what they always have done well. Listen to their customers, create solutions for those customers, and in the case of Druva, for example, being able to be integrated in a Snowball Edge which is unique to Druva, serving those customers, moving data to the cloud but allowing 'em local restore? Give 'em-- >> Andy Jassy announces AWS on-premise which is what we're expecting to see tomorrow. It's maybe some sort of appliance or something along those lines. We'll see what it comes out as. That's essentially the Azure stack model done right. From their premier perspective. Amazon on Amazon, Amazon on-premise, you can run it in the cloud. This sounds like a tailwind for you guys. How will that impact your business? How is Druva going to be impacted? To me, it would seem like it's just, you don't miss a beat. Sounds like it's going to be a good thing. Your thoughts. >> I think as Mike mentioned when he joined the company as well, right? The beauty of, what I didn't even realize, is that every time Amazon improves the platform, Druva is almost automatically benefited, given they're so, they really build on them. So when Amazon announced Snowball Edge, we were a launch partner with them, and third-party apps should be provision on Snowball Edge. I have a different take on the on-premise word than what the world think of. I think ultimately cloud or no cloud, it's all about helping the customer. If my understanding is correct, what Amazon is trying to do is to create a better way for customers to adapt more to public cloud, which is going deep in data center. There's a difference between doing enough on the edge to make the way for the cloud versus trying to do the legacy of going on-premise. So as Amazon creates that corridor for the option, Druva's naturally a good fit for it and part of it. >> Yeah, certainly that being cloud native with AWS is going to give you guys a good lift. Kind of a lay up question there. Let's get into the customer latency question, 'cause this has come up, expect to hear this a lot as well. Latency matters, latency certainly is a key criteria. Why the on-premise strategy? I would say Snowball, they're kickin' the tires. They did the VMware RDS deal on-premise, then so, this was not like an awakening for Amazon, they were going down that road. A little bit more deeper. What is the impact to customers, in you guys' opinion, of the move from Amazon? What's your thoughts? How deep in the enterprise does it go? How will this impact cloud migration? Is it going to change lift-and-shift to be more of a container strategy where you containerize it, then shift it? Some will not shift? What's your thoughts on the impact of cloud on-premise? >> So, I think there's three kinds of clouds. One is where you're trying to build any new applications in cloud which is where mostly Amazon comes in. Second is you can build a pre-made SaaS application. And third is the lift-and-shift. They're trying to still keep it tied to the data center, and putting some local in the cloud. And the third category is where latency matters. And just like virtualization, the last critical app to be virtualized was Exchange and SQL, right? When Exchange got virtualized, the data center opened the door, right? >> Yeah. >> The last critical app left in the way for major clouded option is, seems like Oracle. So which is where our RDS on-premise announced, which is where latency becomes key if you have to adopt some of those financial applications being built in the cloud where hyper-critical latency or uptime is needed. So that's a last hinge for some of the large enterprises to see more clouded option. >> Mike, talk about the product innovations. So people that don't know Druva, they see a lot of hype out there in this market. A lot of advertising, a lot of funding, venture-backed funding, you guys are startup. Pretty competitive. Where are you guys winning? What are the key innovations in the product that you guys have? Take a minute to explain your key value for your customers. >> Well, the first thing I think we want our customers to remember is if you're moving your workloads into an Amazon environment, or you're adopting cloud, we're the only natively architected solution. So just like you would have bought, a competitor for example in the VMware space, you're going to buy Druva because of its advantages to scale with Amazon in terms of its compute, to be able to allow you to tier into the various storage options that they create almost on a quarterly basis for you. But beyond all the infrastructure basics, we are converging services that otherwise were separate silos on-premises. So if you are a customer of one of the legacy providers, and you needed eDiscovery, you bought an eDiscovery product. You needed archive? You bought an archive product. You got backup, you bought backup product. The beauty of having a file system in the cloud is you can buy all of those operations against a single object store. So the definition's changing, we're offering that advantage. >> And one more point to it is also the go-to-market strategy. You saw David McCann this morning talk about Marketplace and how it's going to reshape the selling motion for them. And he mentioned Druva as the key Marketplace partner. With also tooling, or retooling the go-to-market motion of how customers wants to best buy a SaaS service and not a hardware, software model, impacting the real agility and time to market for businesses. >> Are you guys in the Marketplace? >> Absolutely. >> Yeah. >> You guys are on to something really big here and I think it's not well understood, the industry yet. I want to just think out loud for a minute. You mentioned that I got to buy eDiscovery, siloed app. 'Cause that's the old way. I mean, cloud's kind of a horizontally scalable fabric. Some of the best solutions aren't pure plays. So you guys are I think the first company of its kind that kind of is not in a category. I mean, I see how you want to be in a category. Gartner has the Magic Quadrant, backup and recovery, okay. You got to be in some and you win that one, you get some good marks on that. But cloud is more, it helps, maybe it could be leading backup and recovery, but it's not a solution for that. Just delivers value that happens to be for backup and recovery, powered by software. >> That's right. >> So this is the cloud dynamic of having the kind of scale. This is a whole new paradigm of software development. Your reaction to that, do you agree? >> Tell-- >> I totally agree. And I think you hit on two very important points. You know, one is data is a platform in the cloud, now it's a surface that you can operate on. You can add services, you can integrate with ecosystem services. Not everything is going to come from Druva. But unlike competitors, when you are with Druva, we are going to enable you to work with those providers. I think the second one, and the one, personally having come from an ISV environment, is this. If I have a great idea today, 65% of my customers wouldn't be in production with my idea for 2 1/2 years. >> Yeah, the time. >> That model's gone. If Amazon announces a service today as Jaspreet mentions, we want our customers to be taking advantage of that with their data today. >> Talk about the impact of the ecosystem that you guys are seeing, just thoughts on the industry. Jaspreet, you seem to have been around them. You've seen the movie a few times. What's coming? Because if these net-new workloads, again, you're going to hear Andy Jassy talk about this on the keynote tomorrow, new net-new workloads. AI's being powered, ML is being powered by compute availability. So that changes that industry. Kind of a slow, stuck in the mud for 20 years AI. You see Lumi's been around for not new science. But with compute, new magic happens. This the dynamic. What's your thoughts on the ecosystem. Those old solutions are going to die. There's going to be winners and losers. Who are the winners and who are the loser? >> I think the time will say how people take on the challenges. We believe that three core changes coming to cloud. One is serverless computing. In a big way. To drive the cost down of computing dramatically. And also converge the whole networking storage compute in a single mine center. Second is machine learning, or what in Druva we call AI of Things. How machine learning will be like mobility of 10 years ago to impact almost every single piece of software to make it smarter. >> Machine learning first is going to be a new trend. >> Exactly. >> We just called it right now on theCube. ML first. (Mike chuckling) >> And then the third trend is going to be around the nature of enterprise to analyze content. The whole Spark, or Kafka, or, the entire availability of metadata on your fingertips to sort of mine information, the available data, data on the platform, is going to be a predominant thing in the future. So put them together, the possibilities are limitless. You have a data platform which you can mine more cost effectively to the serverless, and be a lot more effective through machine learning. >> I think you guys are a data platform without a doubt. You're not backup and recovery. It's just one of the things you happen to do. And you need a category to start with. I mean, this is a data platform. And you're seeing that all over the place. I just saw a presentation from the FBI, counter-terrorism, they just can't put the puzzles together fast enough on these investigations 'cause the databases are everywhere. So just latency, talk about time to value, just ridiculous. Bad guys are winning. IT is going through the same thing. >> I think software in general has moved away from proprietary and more toward open standards, and so you're going to look for solutions that enable an ecosystem, that don't lock you into a container for one purpose, and we're taking a hold of that trend. >> Alright, guys, real quick, we going to end this segment. What's going on with Druva? Quick plug. How many people? What's on the roadmap? Where's the new innovation, where's the disruption coming? >> You take that? >> Roadmap, 600 people and growing. And the company was just an exciting place to be. Jaspreet mentions one of the most important things. Customer's think about three things. How much does it cost me? It it reducing my risk, or making me more agile? And we're focused on all three. You'll see us, serverless architecture's going to continue to reduce costs. Adopting Amazon storage tiers is going to help our customers reduce costs. From the making them better point of view, you're going to see more eDiscovery, legal hold, performance is going to improve, integration with premises, we got a lot going on at Druva. >> Lambda is so much faster than spitting up an instance, that's for sure. >> That's right, that's right. >> Your thoughts, final word. >> I think data science and machine learning is a big core focus of Druva. I think we have over 100 petabyte in management today. About, as he said, about 600 employees and growing very, very rapidly. How we monetize this 100 petabyte with the cloud through us, with customers, know how our knowledge is a big focus area for us. And also the data born in the cloud. The focus has shifted to your point of newer clouds. How do we tackle the new world clouds? Born in the cloud, born outside the core center of data center, and tackling those. A big focus for us going into next year. >> Congratulations, guys. Jaspreet, I know as founder it's always hard to stand up a company. You guys are doing well, congratulations. You got the right architecture, you got the right product roadmap. Congratulations, I'm looking forward to hearing more. Cloudification, new workloads, scale. This is the new buzzwords around competitive advantage and value. It's theCUBE bringing you all the coverage here from re:Invent. Stay with us for more after this short break. 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