>>Hi, Lisa Martin here with the cube. You're watching our coverage of Dell technologies world. The digital virtual experience. I've got two guests with me here today. We're going to be talking about the university of Piza and how it is leaning into all flash data lakes powered by Dell technologies. One of our alumni is back MERITO, Debbie, and the CTO of the university of PISA. Maricio welcome back to the cube. Thank you. Very excited to talk to you today. CAUTI Gosha is here as well. The director of product management at Dell technologies. Kaushik. Welcome to the cube. Thank you. So here we are at this virtual event again, Maricio you were last on the cube at VMworld a few months ago, the virtual experience as well, but talk to her audience a little bit before we dig into the technology and some of these demanding workloads that the university is utilizing. Talk to me a little bit about your role as CTO and about the university. >>So my role as CTO at university of PISA is, uh, uh, regarding the, uh, data center operations and, uh, scientific computing support for these, the main, uh, occupation that, uh, that, uh, yeah. Then they support the world, saw the technological choices that university of PISA is, uh, is doing, uh, during the latest, uh, two or three years. >>Talk to me about some, so this is a, in terms of students we're talking about 50,000 or so students 3000 faculty and the campus is distributed around the town of PISA, is that correct? Maricio >>Uh, the university of PISA is sort of a, uh, town campus in the sense that we have 20 departments that are, uh, located inside the immediate eval town, uh, but due to the choices, but university of peace, I S uh, the, uh, last, uh, uh, nineties, uh, we are, uh, owner of, uh, of a private fiber network connecting all our, uh, departments and allow the templates. And so we can use the town as a sort of white board to design, uh, uh, new services, a new kind of support for teaching. Uh, and, uh, and so, >>So you've really modernized the data infrastructure for the university that was founded in the middle ages. Talk to me now about some of the workloads and that are generating massive amounts of data, and then we'll get into what you're doing with Dell technologies. >>Oh, so the university of PISA as a, uh, quite old on HPC, traditional HPC. So we S we are supporting, uh, uh, the traditional workloads from, uh, um, CAE or engineering or chemistry or oil and gas simulations. Uh, of course it during, uh, uh, the pandemic year, last year, especially, uh, we have new, uh, kind of work you'll scan, uh, summer related, uh, to the, uh, fast movement of the HPC workload from let's say, traditional HPC to AI and machine learning. And those are the, um, request that you support a lot of remote activities coming from, uh, uh, uh, distance learning, uh, to remote ties, uh, uh, laboratories or stations or whatever, most elder in presence in the past. And so the impact either on the infrastructure or, and the specialty and the storage part was a significant. >>So you talked about utilizing the high performance computing environments for awhile and for scientific computing and things. I saw a case study that you guys have done with Dell, but then during the pandemic, the challenge and the use case of remote learning brought additional challenges to your environment from that perspective, how, how were you able to transfer your curriculum to online and enable the scientists, the physicists that oil and gas folks doing research to still access that data at the speed that they needed to, >>Uh, you know, for what you got, uh, uh, uh, distance learning? Of course. So we were, uh, based on the cloud services were not provided internally by Yas. So we lie, we based on Microsoft services, so Google services and so on, but what regards, uh, internal support, uh, scientific computing was completely, uh, remote dies either on support or experience, uh, because, uh, I can, uh, I, can I, uh, bring some, uh, some examples, uh, for example, um, laboratory activities, uh, we are, the access to the laboratories, uh, was the of them, uh, as much as possible. Uh, we design a special networker to connect all the and to give the researcher the possibility of accessing the data on visit special network. So as sort of a collector of data, uh, inside our, our university network, uh, you can imagine that the, uh, for example, was, was a key factor for us because utilization was, uh, uh, for us, uh, and flexible way to deliver new services, uh, in an easy way, uh, especially if you have to, uh, have systems for remote. So, as, as I told you before about the, uh, network, as well as a white board, but also the computer infrastructure, it was VM-ware visualization and treated as a, as a sort of what we were designing with services either, either for interactive services or especially for, uh, scientific computing. For example, we have an experience with it and a good polarization of HPC workload. We start agents >>Talk to me about the storage impact, because as we know, we talk about, you know, these very demanding, unstructured workloads, AI machine learning, and that can be, those are difficult for most storage systems to handle the radio. Talk to us about why you leaned into all flash with Dell technologies and talk to us a little bit about the technologies that you've implemented. >>So, uh, if I, if I have to think about our, our storage infrastructure before the pandemic, I have to think about Iceland because our HPC workloads Moss, uh, mainly based off, uh, Isilon, uh, as a storage infrastructure, uh, together with some, uh, final defense system, as you can imagine, we were deploying in-house, uh, duty independently, especially with the explosion of the AI, with them, uh, blueprint of the storage requests change the law because of what we have, uh, uh, deal dens. And in our case, it was an, I breathed the Isilon solution didn't fit so well for HB for AI. And this is why we, uh, start with the data migration. That was, it was not really migration, but the sort of integration of the power scaler or flash machine inside our, uh, environment, because then the power scale, all flesh and especially, uh, IO in the future, uh, the MVME support, uh, is a key factor for the storage. It just support, uh, we already have experience as some of the, uh, NBME, uh, possibilities, uh, on the power PowerMax so that we have here, uh, that we use part for VDI support, uh, but off, um, or fleshly is the minimum land and EME, uh, is what we need to. >>Gotcha. Talk to me about what Dell technologies has seen the uptick in the demand for this, uh, as Maricio said, they were using Isilon before adding in power scale. What are some of the changing demands that, that Dell technologies has seen and how does technologies like how our scale and the F 900 facilitate these organizations being able to rapidly change their environment so that they can utilize and extract the value from data? >>Yeah, no, absolutely. What occupational intelligence is an area that, uh, continues to amaze me. And, uh, personally I think the, the potential here is immense. Um, uh, as Maurizio said, right, um, the, the data sets, uh, with artificial intelligence, I have, uh, grown significantly and, and not only the data has become, um, uh, become larger the models, the AI models that, that we, that are used have become more complex. Uh, for example, uh, one of the studies suggests that, uh, the, uh, that for a modeling of, uh, natural language processing, um, uh, one of the fields in AI, uh, the number of parameters used, could exceed like about a trillion in, uh, in a few years, right? So almost a size of a human brain. So, so not only that means that there's a lot of fear mounted to be, uh, data, to be processed, but, uh, by, uh, the process stored in yesterday, uh, but probably has to be done in the same amount of Dinah's before, perhaps even a smaller amount of time, right? So a larger data theme time, or perhaps even a smaller amount of time. So, absolutely. I agree. I mean, those type of, for these types of workloads, you need a storage that gives you that high-performance access, but also being able to store the store, that data is economically. >>And how does Dell technologies deliver that? The ability to scale the economics what's unique and differentiated about power skill? >>Uh, so power scale is, is, is our all flash, uh, system it's, uh, it's, uh, it's bad users, dark techno does some of the same capabilities that, uh, Isilon, um, products use used to offer, uh, one of his fault system capabilities, some of the capabilities that Maurizio has used and loved in the past, some of those, some of those same capabilities are brought forward. Now on this spar scale platform, um, there are some changes, like for example, on new Parscale's platform supports Nvidia GPU direct, right? So for, uh, artificial intelligence, uh, workloads, you do need these GPU capable machines. And, uh, and, uh, Parscale supports that those, uh, high high-performance Jupiter rec machines, uh, through, through the different technologies that we offer. And, um, the Parscale F 900, which should, which we are going to launch very soon, um, um, is, is, is our best hype, highest performance all-flash and the most economic allowed slash uh, to date. So, um, so it is, um, it not only is our fastest, but also offers, uh, the most economic, uh, most economical way of storing the data. Um, so, so ideal far for these type of high-performance workloads, like AIML, deep learning and so on. Excellent. >>So talk to me about some of the results that the university is achieving so far. I did read a three X improvement in IO performance. You were able to get nearly a hundred percent of the curriculum online pretty quickly, but talk to me about some of the other impacts that Dell technologies has helping the university to achieve. >>Oh, we had, uh, we had an old, uh, in all the Dell customer, and if you, uh, give a Luca walk, we have that inside the insomnia, our data centers. Uh, we typically joking, we define them as a sort of, uh, Dell technologies supermarket in the sense that, uh, uh, degreed part of our, our servers storage environment comes from, uh, from that technology said several generations of, uh, uh, PowerEdge servers, uh, uh, power, my ex, uh, Isaac along, uh, powers, Gale power store. So we, uh, we are, uh, um, using a lot of, uh, uh, Dell technologies here, here, and of course, uh, um, in the past, uh, our traditional, uh, workloads were well supported by that technologies. And, uh, Dell technologies is, uh, uh, driving ourselves versus, uh, the, what we call the next generation workloads, uh, because we are, uh, uh, combining gas, uh, in, um, in the transition of, uh, um, uh, the next generation of computing there, but to be OPA who, uh, to ask here, and he was walked through our research of looking for, cause if I, if I have to, to, to, to give a look to what we are, uh, doing, uh, mostly here, healthcare workloads, uh, deep learning, uh, uh, data analysis, uh, uh, image analysis in C major extraction that everything have be supported, especially from, uh, the next next generation servers typically keep the, uh, with, with GPU's. >>This is why GPU activities is, is so important for answer, but also, uh, supported on the, on the, on the networking side. But because of that, the, the, the speed, the, and the, of the storage, and must be tired to the next generation networking. Uh, low-latency high-performance because at the end of the day, you have to, uh, to bring the data in storage and DP. Can you do it? Uh, so, uh, they're, uh, one of the low latency, uh, uh, I performance, if they're connected zones is also a side effect of these new work. And of course that the college is, is, is. >>I love how you described your data centers as a Dell technologies supermarket, maybe a different way of talking about a center of excellence question. I want to ask you about, I know that the university of PISA is SCOE for Dell. Talk to me about in the last couple of minutes we have here, what that entails and how Dell helps customers become a center of excellence. >>Yeah, so Dell, um, like talked about has a lot of the Dell Dell products, uh, today, and, and, and in fact, he mentioned about the pirate servers, the power scale F 900 is, is actually based on a forehead server. So, so you can see, so a lot of these technologies are sort of in the linked with each other, they talk to each other, they will work together. Um, and, and, and that sort of helps, helps customers manage the entire, uh, ecosystem lifecycle data, life cycle together, versus as piece parts, because we have solutions that solve all aspects of, of, of the, uh, of, of, uh, of our customer like Mauricio's needs. Right. So, um, so yeah, I'm glad Maurizio is, is leveraging Dell and, um, and I'm happy we are able to help help more issue or solve solve, because, uh, all his use cases, uh, and UN >>Excellent. Maricio last question. Are you going to be using AI machine learning, powered by Dell to determine if the tower of PISA is going to continue to lean, or if it's going to stay where it is? >>Uh, the, the, the leaning tower is, uh, an engineering miracle. Uh, some years ago, uh, an engineering, uh, incredible worker, uh, was able, uh, uh, to fix them. They leaning for a while and let's open up the tower visa, stay there because he will be one of our, uh, beauty that you can come to to visit. >>And that's one part of Italy I haven't been to. So as pandemic, I gotta add that to my travel plans, MERITO and Kaushik. It's been a pleasure talking to you about how Dell is partnering with the university of PISA to really help you power AI machine learning workloads, to facilitate many use cases. We are looking forward to hearing what's next. Thanks for joining me this morning. Thank you for my guests. I'm Lisa Martin. You're watching the cubes coverage of Dell technologies world. The digital event experience.