(upbeat music) >> We are back, approaching the finish line here at Supercomputing 22, our last interview of the day, our last interview of the show. And I have to say Dave Nicholson, my co-host, My name is Paul Gillin. I've been attending trade shows for 40 years Dave, I've never been to one like this. The type of people who are here, the type of problems they're solving, what they talk about, the trade shows are typically, they're so speeds and feeds. They're so financial, they're so ROI, they all sound the same after a while. This is truly a different event. Do you get that sense? >> A hundred percent. Now, I've been attending trade shows for 10 years since I was 19, in other words, so I don't have necessarily your depth. No, but seriously, Paul, totally, completely, completely different than any other conference. First of all, there's the absolute allure of looking at the latest and greatest, coolest stuff. I mean, when you have NASA lecturing on things when you have Lawrence Livermore Labs that we're going to be talking to here in a second it's a completely different story. You have all of the academics you have students who are in competition and also interviewing with organizations. It's phenomenal. I've had chills a lot this week. >> And I guess our last two guests sort of represent that cross section. Armando Acosta, director of HPC Solutions, High Performance Solutions at Dell. And Matt Leininger, who is the HPC Strategist at Lawrence Livermore National Laboratory. Now, there is perhaps, I don't know you can correct me on this, but perhaps no institution in the world that uses more computing cycles than Lawrence Livermore National Laboratory and is always on the leading edge of what's going on in Supercomputing. And so we want to talk to both of you about that. Thank you. Thank you for joining us today. >> Sure, glad to be here. >> For having us. >> Let's start with you, Armando. Well, let's talk about the juxtaposition of the two of you. I would not have thought of LLNL as being a Dell reference account in the past. Tell us about the background of your relationship and what you're providing to the laboratory. >> Yeah, so we're really excited to be working with Lawrence Livermore, working with Matt. But actually this process started about two years ago. So we started looking at essentially what was coming down the pipeline. You know, what were the customer requirements. What did we need in order to make Matt successful. And so the beauty of this project is that we've been talking about this for two years, and now it's finally coming to fruition. And now we're actually delivering systems and delivering racks of systems. But what I really appreciate is Matt coming to us, us working together for two years and really trying to understand what are the requirements, what's the schedule, what do we need to hit in order to make them successful >> At Lawrence Livermore, what drives your computing requirements I guess? You're working on some very, very big problems but a lot of very complex problems. How do you decide what you need to procure to address them? >> Well, that's a difficult challenge. I mean, our mission is a national security mission dealing with making sure that we do our part to provide the high performance computing capabilities to the US Department of Energy's National Nuclear Security Administration. We do that through the Advanced Simulation computing program. Its goal is to provide that computing power to make sure that the US nuclear rep of the stockpile is safe, secure, and effective. So how we go about doing that? There's a lot of work involved. We have multiple platform lines that we accomplish that goal with. One of them is the advanced technology systems. Those are the ones you've heard about a lot, they're pushing towards exit scale, the GPU technologies incorporated into those. We also have a second line, a platform line, called the Commodity Technology Systems. That's where right now we're partnering with Dell on the latest generation of those. Those systems are a little more conservative, they're right now CPU only driven but they're also intended to be the everyday work horses. So those are the first systems our users get on. It's very easy for them to get their applications up and running. They're the first things they use usually on a day to day basis. They run a lot of small to medium size jobs that you need to do to figure out how to most effectively use what workloads you need to move to the even larger systems to accomplish our mission goals. >> The workhorses. >> Yeah. >> What have you seen here these last few days of the show, what excites you? What are the most interesting things you've seen? >> There's all kinds of things that are interesting. Probably most interesting ones I can't talk about in public, unfortunately, 'cause of NDA agreements, of course. But it's always exciting to be here at Supercomputing. It's always exciting to see the products that we've been working with industry and co-designing with them on for, you know, several years before the public actually sees them. That's always an exciting part of the conference as well specifically with CTS-2, it's exciting. As was mentioned before, I've been working with Dell for nearly two years on this, but the systems first started being delivered this past August. And so we're just taking the initial deliveries of those. We've deployed, you know, roughly about 1600 nodes now but that'll ramp up to over 6,000 nodes over the next three or four months. >> So how does this work intersect with Sandia and Los Alamos? Explain to us the relationship there. >> Right, so those three laboratories are the laboratories under the National Nuclear Security Administration. We partner together on CTS. So the architectures, as you were asking, how do we define these things, it's the labs coming together. Those three laboratories we define what we need for that architecture. We have a joint procurement that is run out of Livermore but then the systems are deployed at all three laboratories. And then they serve the programs that I mentioned for each laboratory as well. >> I've worked in this space for a very long time you know I've worked with agencies where the closest I got to anything they were actually doing was the sort of guest suite outside the secure area. And sometimes there are challenges when you're communicating, it's like you have a partner like Dell who has all of these things to offer, all of these ideas. You have requirements, but maybe you can't share 100% of what you need to do. How do you navigate that? Who makes the decision about what can be revealed in these conversations? You talk about NDA in terms of what's been shared with you, you may be limited in terms of what you can share with vendors. Does that cause inefficiency? >> To some degree. I mean, we do a good job within the NSA of understanding what our applications need and then mapping that to technical requirements that we can talk about with vendors. We also have kind of in between that we've done this for many years. A recent example is of course with the exit scale computing program and some things it's doing creating proxy apps or mini apps that are smaller versions of some of the things that we are important to us. Some application areas are important to us, hydrodynamics, material science, things like that. And so we can collaborate with vendors on those proxy apps to co-design systems and tweak the architectures. In fact, we've done a little bit that with CTS-2, not as much in CTS as maybe in the ATS platforms but that kind of general idea of how we collaborate through these proxy applications is something we've used across platforms. >> Now is Dell one of your co-design partners? >> In CTS-2 absolutely, yep. >> And how, what aspects of CTS-2 are you working on with Dell? >> Well, the architecture itself was the first, you know thing we worked with them on, we had a procurement come out, you know they bid an architecture on that. We had worked with them, you know but previously on our requirements, understanding what our requirements are. But that architecture today is based on the fourth generation Intel Xeon that you've heard a lot about at the conference. We are one of the first customers to get those systems in. All the systems are interconnected together with the Cornell Network's Omni-Path Network that we've used before and are very excited about as well. And we build up from there. The systems get integrated in by the operations teams at the laboratory. They get integrated into our production computing environment. Dell is really responsible, you know for designing these systems and delivering to the laboratories. The laboratories then work with Dell. We have a software stack that we provide on top of that called TOSS, for Tri-Lab Operating System. It's based on Redhead Enterprise Linux. But the goal there is that it allows us, a common user environment, a common simulation environment across not only CTS-2, but maybe older systems we have and even the larger systems that we'll be deploying as well. So from a user perspective they see a common user interface, a common environment across all the different platforms that they use at Livermore and the other laboratories. >> And Armando, what does Dell get out of the co-design arrangement with the lab? >> Well, we get to make sure that they're successful. But the other big thing that we want to do, is typically when you think about Dell and HPC, a lot of people don't make that connection together. And so what we're trying to do is make sure that, you know they know that, hey, whether you're a work group customer at the smallest end or a super computer customer at the highest end, Dell wants to make sure that we have the right setup portfolio to match any needs across this. But what we were really excited about this, this is kind of our, you know big CTS-2 first thing we've done together. And so, you know, hopefully this has been successful. We've made Matt happy and we look forward to the future what we can do with bigger and bigger things. >> So will the labs be okay with Dell coming up with a marketing campaign that said something like, "We can't confirm that alien technology is being reverse engineered." >> Yeah, that would fly. >> I mean that would be right, right? And I have to ask you the question directly and the way you can answer it is by smiling like you're thinking, what a stupid question. Are you reverse engineering alien technology at the labs? >> Yeah, you'd have to suck the PR office. >> Okay, okay. (all laughing) >> Good answer. >> No, but it is fascinating because to a degree it's like you could say, yeah, we're working together but if you really want to dig into it, it's like, "Well I kind of can't tell you exactly how some of this stuff is." Do you consider anything that you do from a technology perspective, not what you're doing with it, but the actual stack, do you try to design proprietary things into the stack or do you say, "No, no, no, we're going to go with standards and then what we do with it is proprietary and secret."? >> Yeah, it's more the latter. >> Is the latter? Yeah, yeah, yeah. So you're not going to try to reverse engineer the industry? >> No, no. We want the solutions that we develop to enhance the industry to be able to apply to a broader market so that we can, you know, gain from the volume of that market, the lower cost that they would enable, right? If we go off and develop more and more customized solutions that can be extraordinarily expensive. And so we we're really looking to leverage the wider market, but do what we can to influence that, to develop key technologies that we and others need that can enable us in the high forms computing space. >> We were talking with Satish Iyer from Dell earlier about validated designs, Dell's reference designs for for pharma and for manufacturing, in HPC are you seeing that HPC, Armando, and is coming together traditionally and more of an academic research discipline beginning to come together with commercial applications? And are these two markets beginning to blend? >> Yeah, I mean so here's what's happening, is you have this convergence of HPC, AI and data analytics. And so when you have that combination of those three workloads they're applicable across many vertical markets, right? Whether it's financial services, whether it's life science, government and research. But what's interesting, and Matt won't brag about, but a lot of stuff that happens in the DoE labs trickles down to the enterprise space, trickles down to the commercial space because these guys know how to do it at scale, they know how to do it efficiently and they know how to hit the mark. And so a lot of customers say, "Hey we want what CTS-2 does," right? And so it's very interesting. The way I love it is their process the way they do the RFP process. Matt talked about the benchmarks and helping us understand, hey here's kind of the mark you have to hit. And then at the same time, you know if we make them successful then obviously it's better for all of us, right? You know, I want to secure nuclear stock pile so I hope everybody else does as well. >> The software stack you mentioned, I think Tia? >> TOSS. >> TOSS. >> Yeah. >> How did that come about? Why did you feel the need to develop your own software stack? >> It originated back, you know, even 20 years ago when we first started building Linux clusters when that was a crazy idea. Livermore and other laboratories were really the first to start doing that and then push them to larger and larger scales. And it was key to have Linux running on that at the time. And so we had the. >> So 20 years ago you knew you wanted to run on Linux? >> Was 20 years ago, yeah, yeah. And we started doing that but we needed a way to have a version of Linux that we could partner with someone on that would do, you know, the support, you know, just like you get from an EoS vendor, right? Security support and other things. But then layer on top of that, all the HPC stuff you need either to run the system, to set up the system, to support our user base. And that evolved into to TOSS which is the Tri-Lab Operating System. Now it's based on the latest version of Redhead Enterprise Linux, as I mentioned before, with all the other HPC magic, so to speak and all that HPC magic is open source things. It's not stuff, it may be things that we develop but it's nothing closed source. So all that's there we run it across all these different environments as I mentioned before. And it really originated back in the early days of, you know, Beowulf clusters, Linux clusters, as just needing something that we can use to run on multiple systems and start creating that common environment at Livermore and then eventually the other laboratories. >> How is a company like Dell, able to benefit from the open source work that's coming out of the labs? >> Well, when you look at the open source, I mean open source is good for everybody, right? Because if you make a open source tool available then people start essentially using that tool. And so if we can make that open source tool more robust and get more people using it, it gets more enterprise ready. And so with that, you know, we're all about open source we're all about standards and really about raising all boats 'cause that's what open source is all about. >> And with that, we are out of time. This is our 28th interview of SC22 and you're taking us out on a high note. Armando Acosta, director of HPC Solutions at Dell. Matt Leininger, HPC Strategist, Lawrence Livermore National Laboratories. Great discussion. Hopefully it was a good show for you. Fascinating show for us and thanks for being with us today. >> Thank you very much. >> Thank you for having us >> Dave it's been a pleasure. >> Absolutely. >> Hope we'll be back next year. >> Can't believe, went by fast. Absolutely at SC23. >> We hope you'll be back next year. This is Paul Gillin. That's a wrap, with Dave Nicholson for theCUBE. See here in next time. (soft upbear music)

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation. >> Hi, I'm Peter. Boris, And welcome to another cube conversation from our wonderful studios and beautiful Paolo Alto, California. One of the biggest challenge that every enterprises faces how to attend to the volumes of data that are being generated by applications. But more importantly, that the business is now requiring because they want to find new derivative sources of value in their digital business. Transformations is gonna require a significant retooling and rethinking of how we used eight is an asset. And the directions that infrastructure, data management and business are gonna move together over the course of next few years. Now, have that conversation. Got a couple of great guests here. Josie Swoop is a VP of marketing veritas. Welcome to Cuba or back to the Cube. Yeah, thanks. Peter and Rick Clark is a CEO of opt are welcome. Thank you for the first time. >> Great to be here, >> So let me start here. Joey, why don't we start with you? Give us a quick update on Veritas and where your customers are indicating the direction needs to go. >> We've just had, ah, record breaking financial year for us, which ended in end of March. So since divestiture from semantic, as you know better, Toss has been through a transformation and then on a path to growth. So our core businesses are humming with just like I said, the second half of the year specifically was great for us. What we're hearing from customers, Peter, is that they want to elevate their their business problems away from infrastructure to business outcomes. That what they ask veritas to do is, can you abstract away some of those infrastructure plumbing problems, storage, security, data protection and focus on what the applications can give us. That's number one. Number two is Can we standardize? I mean, the example of Southwest comes to mind, right? They have the same plane so they can reroute those planes anytime they have the same pilots flying those planes so they can to standardize. So they collapsed better. And then, lastly, to your point value of data over volume. Everybody talks about the volume. What about the value of data? What is veritas do for for me? Mr. You know God's a customer in our tax extract value of that data, which is growing day by day. >> Well, one of the most interesting things about this challenge of businesses faces they try to attend to these things is that data is often characterizes the new oil. And we we push back against that Because >> data is a new kind of asset, it's an asset that's easily copied. It's an asset that's easily shared. You can easily integrate it. You can apply it to multiple uses with zero loss of fidelity and what it does currently. And so the whole notion of creating new options in the value of data's intrinsic to the questions of digital business. So that suggests that we need to start thinking Maur about data protection, not just from the standpoint of protecting data once it's been created and is sitting there so we can recover it. But new types of utilization, new ways of thinking about data data as it's going to be used, understanding more about dating, protecting that Rick, would you kind of Does that resonate? >> Yeah, absolutely. You know, one of the things that we've sort of seed in the marketplace is certainly over the last 10 years, the Data Sena has become so complex. This is massive fragmentation of data across highly virtualized infrastructures. And then, when public clouds came along, customers didn't really know what workloads they should move up into those clouds. And so what we saw is a huge problem. Is areas of cost and efficiencies, massive problems of risk and then obviously the amount of money that cos of spending on compliance. And so what we were really focusing on is the gaps. What do you not know about? And so we would really >> about your data >> about your data. Exactly. So we really measure the hot beat off the data protection environment, and from that we could actually see where are you? Risk where your exposure, where you're spending too much money, >> Where's your opportunities? Seize your opportunities. So we've got a notion of the the solution that folks are looking for, something that provides greater visibility into their end and data from a risk exposure opportunity. New sources of utilization standpoint talk a bit about how >> at four >> rounds out the veritas portfolio as it pertains of these things that you're seeing customers asked for taking data closer to outcomes and away from the device orientation? >> Absolutely. So Vatos has always been known to be a leader and data protection. We've done that for over 20 years. We also were the first pioneers in software defined storage. And we're number one in market share, according to I. D. C and Gardner as well. Ah, but again to my earlier point, customers have been asking. So what? We've done the plumbing really well and you've scaled. How do you take this to the next level? Extract value from all that data you're sitting on top of that you're protecting. And that's where apt are comes into the picture. We've built some tools natively within veritas of the last three or four years where we try to go and classify the data on in jest, identify things like P I information sensitive data, rock data, redundant, obsolete, trivial data that we can delete. There was a customer who recently deleted 30,000,000 files, just press the delete button and this isn't a highly regulated environment, >> but they were still pretty darn eggs. >> They definitely where but we were able to give them that visualization and information that they required. Now the question those customers are asking us or we're asking us. Before avatar came into the picture was at the infrastructure level. How do I know how much I'm spending on my data protection environments? Do I know where the growth ISS is it all in the traditional workloads of oracle ASAP, Or is it in virtual or is it in the cloud? Right. Am I putting too much data on tape? Is it costing me enough? Can extract the value from that data. So they were asking us infrastructure visualization and i D analytics. Questions which only apt are could answer. And we have some joint customers they were actually using. Apt are already not just with to monitor the vatos ecosystem, but even some of our competitors and the broader i t ecosystem on a single planet class. And that's where I think after really shines is is the agnostic approach they take beyond just veritas are beyond just another storage vendor. >> Well, so way certainly subscribed to this notion that data protection is going to It's gonna be extended, but it's gonna become a strategic digital business capability that does have to be re funk around the concept of data value and sounds like that's the direction you're taking, and you guys have clearly seen that as well. But obviously some of your customers have seen it. So talk to us a little bit about how customers helped you two guys together. >> Yeah, that's a great question. Was interesting. Actually. We had some of the largest companies in the globe actually using ourself with many of the fortune Tien using up self with J. P. Morgan Chase quote calm Western digital. And they came to us with these very precise problems around, you know, howto optimize my risk within the environment, had a streamline, obviously the costs and compliance. And we found that they were very common questions. And so we actually created this agnostic intelligence built into the software a rules engine that would have to correlate data from all of these disparate data sources. Whether Tom primer on the cloud tying that together would provide impactful insights to our customers that could sold real world problems. And we'll do it with kind of what we call the easy button. One of the big problems with a lot of software products out there today. Is there a point solutions to manage pots of the infrastructure companies wanted a single pane of glass where I could see everything across all of my storage. All of my data protection on prim and cloud. And that's really what we bring to the table, that single paying the class. And we do it very simply at scale for the largest customers. And that's in many ways was the synergy, obviously, with a partnership with Veritas. >> So give us some sense of how how customers will see the benefits of this from a rollout standpoint over the next 6 to 18. >> Right? So Step One in this journey for us is to ensure there are customers. Understand that we're going to continue to have that open an agnostic approach Apt are suddenly is not gonna become proprietary batter toss product. It's going to continue on its on its mission to be agnostic across various storage data protection and cloud environments. That's number one. Number two is we're gonna bring the the artificial intelligence and machine learning capabilities that we have in house with Veritas combined that with some of the things that Rick just docked, abide with the capabilities adapt our has combine, it's our customers can gain. I know add value. The one plus one equals three approach there as well. So those air, like the two key pillars for us going forward and eventually will extend apt are to an end to in Data Analytics platform not just I d analytics, where we're looking at infrastructure, but an end to end data. Plus I t analytics platform that spans Veritas is will Is the broader a IittIe ecosystem? >> Well, so it's good to hear that you're gonna let apt are continue to focus on data value as opposed to veritas value. Right talk. Talk to me a little bit. About what Does that analytics piece really mean? Howard Customers going to use it? How are they using it today? How are they gonna >> let me carry that? Said is roughly 30,000 unique metrics that we actually gather across the whole I t infrastructure and we'll look at a classic use cases. One of exposure. What? A lot of companies been enormous amount of money on the data protection infrastructure. The using disparity, tools and technologies they don't always go with. One platform like net backup is an example, right? And so with that, come challenges because there's gonna be gaps they might be backing up a Windows server where they're the backup policy says they're just backing up. The C drive will interrogate VM, where all the hyper visor will look at the network and see that there's a D Dr attached to that volume as well. And there's no backup data protection policy. So enormous amount of exposure if they tried to do a restore, obviously, from the d Dr where there's no protection, right from a cost perspective, there's an enormous amount of white space problem in the storage industry. More and more companies are moving from spinning distal flash arrays. A lot of companies is struggling with How do I protect those old flash A raise the using snapshots that using cloud they're tearing to the cloud the using different backup products. Obviously, we'd prefer that they used their backup, but with our software, we can provide that that inside across the entire data protection framework and storage and show you where is your risk? Where is your inefficiency, where you double protecting things into spending too much, much money? This whole notion of data protection is transaction. A lot of people do what's called distant, distant eight still being voted off site. How do you know that all those transactions are successful? How do you know you can restore based on those s L A's and tying that into you? See, M d B. That's what appetite does. >> So I'ma throw a little bit of a curveball here. So having worked within 90 worked with N i t organizations, it can be I ke historically can has been rolled to the compartmentalizing segment you administrated for servers in Australia for storage of people who are administrating applications and and subsystems. And the cloud is munge ing a fair amount of that together. But one of the places that has always required coordination, collaboration and even more important practice has been in the area of restore firms were shops that did not practice how they would restore, you know, hopefully they never had a problem. But if they did have a problem, if they hadn't practiced that process, they would likely we're not gonna be successful in bringing the business up. Gets even more important digital business. Can you give us a little bit of visibility into how this combination taking the metadata, the metrics of visibility. Taking the high quality service is bringing them together is going to streamline, restore within their prices. >> So first, let me address the first point you made, which is what I call the rise of the versatile is too right. So there are no more specialists in certain jobs. The versatile listen, the cloud or in virtual tend to do three or four jobs when there's back up our story virtualization itself on DDE. What the's Verceles want is to explain an easy barton to restore their VM environment or their big data. And my mother there Hadoop environment. They're not really worried. As a central I t. Team that Hey, what am I going to do with the entire data estate? How did I restore that? So that's the first step. Second step, as the world of I t gets more more complicated on the rise of the worst list continues to happen. Thes folks want to be able to have a resiliency plan. They want to be able to rehearse these restores right, and if they don't have a resiliency plan built in if the data protection is so siloed and does not help them build a resiliency plan. And to end that restore is not gonna be successful. Likely? Right. And that's where Veritas and companies like Veritas come in to help them build those resiliency plans and to end. >> But let me take you back to so the financial industry, for example, there are rules about how fast you you have to be able to restore. I gotta believe that visibility into data that is a value level can help set priorities. Because sometimes you want to bring up this application of this class of applications of this class of users of functions before you bring up those so does does apt are apt are going to provide even greater clarity in the crucial restore >> at 70. One of the biggest challenges for >> a lot of companies with restores is actually finding the data. We had a classic use case with a large Fortune 10 company where they had a bunch of service that were being backed up. There were bolted off the tape, and then it was obviously a different backup product they were using. The actually lost the catalog. The data was still there on tape. They had millions of tapes in the vaults, and they used apt title, identify the barcodes and recover that data literally within a matter of hours. And so not only can we find you your freshest copy the most recent copy, if that's what you want, but we can find where is your data? Because in a lot of cases there's multiple replications, multiple copies of the data across all sorts of assets within your >> infrastructure. Interesting. So last thoughts. When we have you back in the Cube in a year, Where you guys going? Big? >> Hey, listen, the two things that I talked about we're going to continue to expand the support of the ecosystem. The world of I t. Whether it's on Prem virtual or in the cloud with Apt are we? We're going to continue to invest in the artificial Intelligence and ML capabilities are not just apt are but all of that tosses ecosystem and you'll see amore integrated approach on the platform based approach on standardization When we come here >> next, guys, thank you so much. Great conversation. Thanks for being here in the Cube to talk about this important relation between data tooling and sources of business value. Rick Clark is the vice president of the outdoor business unit. Used to be the CEO of actor, but now the vice president. The outdoor business unit Veritas. Josie Stroop is vice president of marketing of Veritas. Once again, guys, thanks very much for being here. Thank you so much for having us. And once again, I'm Peter Burgers. You've been listening to another cube conversation until next time.