>>Hey, welcome to this cube conversation with Dell technologies. I'm Lisa Martin. I've got kosha ghost here with me. He's back on the cube director of product management for unified NAS solutions at Dell technologies. CATIA. Great to see you again. >>Yes. I raped a great to be here again. >>We're going to be talking about the major announcement that Dell technologies just made with their scale-out file storage system that has Dell EMC power scale. We're going to unpack the recent announcement, new features, capabilities, all that good stuff. Kaushik let's go ahead and start. Just give us that high level view of Dell EMC power scale. >>Yes, absolutely. Itself power scale is a high-performance scale-out file storage solution. Um, it's the successor to the Isilon family record, which as you guys know, I mean, there's one of the leading file solutions in the market today. Um, power scale one best, which is the file system that runs on power scale and also the Isilon family, um, is offers an exceptional simplicity, flexibility, and performance, um, which is what Isilon and Parscale is known for. I mean, um, if you look at Gardner's magic ordered one, Fs has been listed as the leader in that, uh, in the distributed and object file system. So, uh, so that basically is now our scaled. We launched our first Parscale all flash products last year. And then this year with this launch, we are sort of completing that portfolio, um, with, uh, with new hybrid and archive, uh, platforms. >>Excellent. And we're going to get into that as well. Let's go ahead and start unpacking this announcement. Walk me through some of the key things that are new and announced in this recent announcement. >>Yeah, except we just launched the hybrid archive platforms, um, on, as part of the Parscale family, are there two archive platforms and two hybrid platforms that we launched and, uh, they offer better CPU, performance, cash, and all that stuff, but, but we don't want to go into the speeds and feeds what I really want to hide breast is the, is the software capabilities that is far skull rings for starters. Um, it is, uh, it now includes inline data compression in 99 reduction. It's all built into it. Um, we support now new ransomware protection capabilities with, uh, with this product. Um, there's a new data protection capability that we now support with our, um, with our, our protected data data manager. Um, and, um, and then the, all the goodness of, uh, Iceland, one Fs and Parscale one Fs that sort of continues. >>I imagine, since the launch last year, cash took a lot of customer conversations that helped to drive this launch and the complete transition on the innovation of what we now see as power scale. >>Yeah. Yeah. I mean, uh, there, there have been some great conversations. People have been, um, people have been really waiting for this product offering because now, uh, they can basically combine those flash platforms that we launched last year with these hybrid platforms and can offer a really a solution that only gives you that performance, but also the, the cost and, uh, savings and the value that, um, that, uh, only our powers skill in Iceland can give you, >>Give me a good overview of some of those key capabilities that the existing Isilon customers and the prospective new customers of power scale are going to be able to take advantage of. >>Yes. So the new, some of the new capabilities as in line efficiency, as I mentioned earlier, that's now built into the product. Um, we have a line efficiency today on our all flash platforms. Uh, so now introducing it with these hybrid and archived nodes, what that means is that when you set up a mixed cluster with all flash and hybrid, when you gear the data down from the national hybrid, the data does not have to be rehydrated. They stay compressed, they stay in protected and so on and so forth. So that's one big advantage that you get. Second, um, these power skill hybrid type platforms were built ground up, uh, with our own custom hardware, unlike the flashback phones with be leverage powered servers for these ones, we use our custom hardware. And the reason for that is because what those archive and storage, the whole story we want that density, we can store up to 500 terabytes of usable capacity, effective usable capacity in, in these archive nodes in a single, uh, one U rack unit. And then, uh, of course, uh, from a software perspective, uh, we talked about ransomware protection. So, so we have a new capability with trends of bear protection. And then there's this new capability that we just launched in regard to backups, more efficient, more faster backups with, uh, with our, our protector will be bought predict family of products. >>Excellent. I want to dig into the ransomware and data protection in a minute, but I want to get a sense of the overall theme of the launch. You talked about this being the completion of that tech refresh some of the new capabilities and enhancements that customers are going to be able to take advantage of it. Give me that higher level kind of thematic look at this news. >>The big team of this is basically finishing that Parscale family that we started last year, right? So we started with launching the whole flash. Now with this hybrid and archive. Now we have the flu family done, um, all products, not support in line efficiency, so we can move the data around, you get the same, uh, data doesn't get high rehydrated. Um, you are, you can make it part of a single cluster. Um, and you get all the performance benefits, um, the scalability benefits of one Fs, um, and new data management capabilities, the, um, so all of that, that we started all of that goodness that we started with our skill, all flash. Um, we soft, continued now with this, uh, with this platform. >>Got it. And I know you guys did your own internal study and I'd like you to share some of the results with the audience, you guys compared power scale to competitors in traditional NAS in flash only NAS in mixed NAS, San and software only NAS give us a snapshot into what some of those results were for power scale. >>Yeah. I mean, uh, the big take away out here is that, um, that when it comes to power scale, um, they, we don't have a competitor when it comes to scalability, right? Uh, the fact that you can now work, uh, on petabytes of capacity under a single namespace, a single file system, and also give you that performance. Um, we, there is none to today, right? And, um, and then there may be some which can do those also, but then they don't have the enterprise capabilities like replication, um, and, uh, the rich enterprise capabilities that one, if fit, sets so off performance, scale capabilities and all the, uh, the simplicity of one Fs. And that's basically what the unique thing about our skaters >>W performance scale and simplicity, three things that I'm sure enterprises, small, medium businesses in any industry appreciate you. You talked about the, um, what's new in terms of the hybrid notes and the archive nodes. Can you help us understand what workloads does nos are best targeted for? >>Absolutely so hybrid and archive. What we have realized is that not every data can be a compressed RDU, right? So, so it's not, we would love customers to use our all flash products. They get the deduplication, they get the compression, then it lowers the cost. And clearly then you get the performance and the cost, but there are workloads like media and entertainment, video surveillance, where you will not be able to compress or that guest, rather than it being for a very expensive flash. You could put those data sets in our lower cost archive platforms as an example. And if you have situations where look, I need some performance, but there is a lot of old data and you can actually mix and match it also. So you're going to have those flash platform is giving that performance. And then you have our archive platforms, which is basically giving you the lowest cost storage for that data. And it is not so frequent giving access. >>And there's the flexibility there. So how can, this is the tech refresh? He said, this has been completed now a power scale from Isilon. How can existing Isilon customers take advantage? What are their next steps to be able to take advantage of the newer capabilities and technologies? >>Yeah, absolutely. I mean, one thing we, we, our scale has it, that's very different from others is that Parscale has this mantra called the no, no left behind. So if you are an existing Isilon customer, you can basically add these Parscale nodes to your existing Iceland cluster without breaking any donut. Then we put our scale, we lock them, magically redistribute, rebalance your workloads across these new nodes. And you sort of keep on expanding our cluster. And when you, when you feel like that, you can, uh, take out the older nodes, uh, at the time of your choosing, right? So that stuff, um, that's a huge benefit that we get. So in fact, in some customer environments, their data has been there for almost 10 to 12 years now, uh, uh, because they've never had to do a forklift upgrade. So that sort of continues with this family. Um, if you learn to learn more about it, I would encourage, uh, going to Dell technologies slash power scale, uh, or contact your Dell technologies, uh, rep >>Let's kind of wrap up things here with talking about, dig into ransomware. We've seen ransomware become a household word, the colonial pipeline, the meat packing organization that was attacked earlier this summer. We know that that a lot of data show that there's a one ransomware attack happens every 11 seconds. And of course we only hear about the really big attacks. Um, I've had the opportunity to talk to a lot of cybersecurity leaders lately, and they're showing that ransomware is up, you know, at least 10 X in the last year with this massive pivot to work from home now, work from anywhere. Talk to me about some of the focus that Dell has put in power scale now with perspective of ransomware protection and recovery. >>Yeah. So for ransomware product, we have to do things that we are doing. So one is this concept of a detection. So when an attack is happening, we want it to be able to detect with date at an attack is happening and take some corrective measures, right? And so we have this product called Sabrina eyeglass, which is exclusively built for, uh, uh, built for, uh, uh, our scale and using this product they use, we use AIS, uh, to basically to figure out that if an attack is happening, we detect it. And based on that based on policies, we can then either, if it's happening with only one user, we can start off, um, uh, start off, uh, prevent, uh, sort of lock it down that particular user profile or, or take other corrective actions taking meaning set up. So that's one aspect of it, which is about the detection of it and taking some quick steps. >>Then there's a second aspect of it, which is all about recovery, right? So, so we do have a replications event. If the customer chooses, we can have reputations set up from your Parscale, uh, production cluster to another cluster. And, um, and in that replication, uh, we can introduce an air gap so that, uh, any, anything bad thing is happening here does not get, uh, uh, does not get replicated to that, uh, remote in mine. So, um, so, so those are the two ways, one detecting, and second basically protecting it. Um, and not only just protecting it, but ensuring that air gap, um, capabilities, data as well, so that, uh, the ransom reason not replicated there as well. >>Absolutely critical. Given some of the things that you and I mentioned a few minutes ago in terms of the explosion of ransomware, which hopefully in our remote, remote work hybrid environment, as more technologies like this come out from Dell technologies and its partners, we'll start to see those ransomware numbers go down. Lastly, I want you to just restate, you mentioned a URL where folks can go to learn more information. Now you've got several different links to point folks to, can you go ahead and remind us what those are again? >>Yes, absolutely. I mean, uh, the easiest you are to go to is Dell technologies slash flower scale. I mean, if you're, that's a one-to-one URL and I'd like you to remember, once you go there, there'll be videos, articles, blogs, and you can, uh, look through a much going and then whatever you want from them. >>Excellent contract. Thank you for joining me today. Talking to me about what's new with power scale, congratulations on the completion of the refresh, a lot of new capabilities and, and, uh, technologies that your customers, existing Isilon and feature perspective, power scale customers are going to be able to take advantage of, look forward to hearing in the next few months in customer success stories. Thanks for your time. Thank >>You >>For Casha gauche. I'm Lisa Martin. You're watching a cube conversation.

>>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.

(upbeat music) >> Hi, Lisa Martin here with theCUBE. 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 Pisa and how it is leaning into all flash deal that is powered by Dell Technologies. One of our alumni is back, Maurizio Davini, the CTO of the University of Pisa. Maurizio, welcome back to theCUBE. >> Thank you. You're always welcome. >> Very excited to talk to you today. Kaushik Ghosh is here as well, The Director of Product Management at Dell Technologies. Kaushik, welcome to theCUBE. >> Thank you. >> So here we are at this virtual event again. Maurizio, you were last on theCUBE at VM world a few months ago, the virtual experience as well. But talk to our 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 regarding the data center operations and scientific computing support. It is the main occupation that I have. Then I support also, the technological choices That the University of Pisa is doing during the latest two or three years. >> Talk to me about something, so this is 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, Maurizio? >> The University of Pisa is sort of a town campus in the sense that we have 20 departments that are located inside the medieval town, but due to the choices that University of Pisa has done in the last '90s, we are owner of a private fiber network connecting all our departments and all our (indistinct). And so we can use the town as a sort of white board to design new services, new kind of support for teaching and so on. >> 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, Maurizio, 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 has a quite old historian HPC, traditional HPC. So we are supporting the traditional workloads from CAE or engineering or chemistry or oil and gas simulations. Of course, during the pandemic year, last year especially, we have new kind of workload scan, some related to the fast movement of the HPC workload from let's say, traditional HPC to AI and machine learning. And also, they request to support a lot of remote activities coming from distance learning to remotize laboratories or stations or whatever, most elder in presence in the past. And so the impact either on the infrastructure or, and especially on the storage part, was significant. >> So you talked about utilizing the high performance computing environments for a while 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 were you able to transfer your curriculum to online and enable the scientists, the physicists, the oil and gas folks doing research to still access that data at the speed that they needed to? >> You know, for what you got distance learning, of course, we were based on cloud services that were not provided internally by us. So we based on Microsoft services, on Google services and so on. But what regards internal support, scientific computing was completely remotized, either on support or experience, because how can I bring some examples? For example, laboratory activities were remotized. The access to the laboratories was (indistinct) remote as much as possible. We designed a special network to connect all the laboratories and to give the researcher the possibility of accessing the data on this special network. So a sort of a collector of data inside our university network. You can imagine that... Utilization, for example, was a key factor for us because utilization was, for us, a flexible way to deliver new services in an easy way, especially, if you have to administer systems for remote. So as I told you before about the network as a white board, also, the computer infrastructure was (indistinct) utilization treated as a sort of (indistinct). We were designing new services, either for interactive services, or especially for scientific computing. For example, we have an experience with utilization of HPC workload, storage and so on. >> Talk to me about the storage impact because as we know, we talk about these very demanding unstructured workloads, AI, machine learning, and those are difficult for most storage systems to handle. Maurizio, 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 if I have to think about our storage infrastructure before the pandemic, I have to think about Isilon, because our HPC workloads was mainly based off Isilon as a storage infrastructure. Together, with some final defense system, as you can imagine, we were deploying in our homes. During the pandemic, but especially with the explosion of the AI, the blueprint of the storage requests changed a lot because what we had until then, and in our case, was an hybrid Isilon solution. Didn't fit so well for HB, for AI (indistinct) and this is why we started the migration. It was not really migration, but the sort of integration of the Power Scale or flash machine inside our environment, because then the Power Scale or flash, and especially, I hope in the future, the MVME support is a key factor for the storage, storage support. We already have experienced some of the MVME possibilities on the Power Max that we have here that we use (indistinct) and part for VDI support, but flash is the minimum and MVME is what we need to support in the right way the AI workloads. >> Lisa: Kaushik, talk to me about what Dell Technologies has seen. The optic the demand for this. As Maurizio said, they were using Isilon before, adding in Power Scale. What are some of the changing demands that Dell technologies has seen and how does technologies like Power Scale and the F900 facilitate these organizations being able to rapidly change their environment so that they can utilize and extract the value from data? >> Yeah, no, absolutely. Artificial intelligence is an area that continues to amaze me and personally, I think the potential here is immense. As Maurizio said, right? The data sets with artificial intelligence have grown significantly, and not only the data has become larger, the models, the AI models that are used have become more complex. For example, one of the studies suggests that for a modeling of natural language processing, one of the fields in AI, the number of parameters used could exceed like a trillion in a few years, right? So almost the size of a human brain. So not only that means that there's a lot of data to be processed, but the process stored ingested, but probably has to be done in the same amount of time as before or perhaps even a smaller amount of time, right? So larger data, same time, or perhaps even a smaller amount of time. So, absolutely, I agree. For these types of workloads, you need a storage that gives you that high-performance access, but also being able to store that data economically. >> Lisa: And Kaushik, how does Dell technologies deliver that? The ability to scale the economics. What's unique and differentiated about Power Scale? >> So Power Scale is our all flash system. It uses some of the same capabilities that Isilon products used to offer. The 1 FS file system capabilities. Some of the same capabilities that (indistinct) has used and loved in the past. So some of those same capabilities are brought forward now. on this Power Scale platform. There are some changes, like for example, our new Power Scale platform supports NVDR GPU direct, right? So for artificial intelligence workloads, you do need these GPU capable machines and Power Scale supports those high-performance GPU direct machines through the different technologies that we offer, and the Power Scale F 900, which we are going to launch very soon is our best highest performance all flash and the most economical all flash to date. So it not only is our fastest, but also offers the most economical way of storing the data. So ideal for these type of high-performance workloads, like AIML, deep learning and so on. >> Excellent. Maurizio, 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 is helping the University to achieve. >> Oh, we are an old Dell customer and if you give a look what we have inside our data centers, we typically joking. We define as a sort of Dell technologies supermarket in the sense that the great part of our servers storage environment comes from Dell technology. Several generations of Power Edge servers, Power Max, Isilon, Power Scale, Power Sore. So we are using a lot of Dell technologies here, and of course, in the past, our traditional workloads were well supported by Dell technologies. And Dell technologies is driving us versus what we call the next generation workloads, because they are accompanying us in the transition versus the next generation computing, but to hope to adhere and (indistinct) to our researchers are looking for, because if I had to give a look to what we are doing mostly here, healthcare workloads, deep learning, data analysis, image analysis, same major extraction. Everything have to be supported, especially from the next generation servers, typically to keep with GPUs. This is why GPU direct is so important for us, but also, supported on the networking side, because the speed of the storage must be tied to the next generation networking. Low latency, high performance, because at the end of the day, you have to bring the data to the storage room, and typically, you do it by importing it. So they're one of the low latency, high performance interconnections. Zones is also a side effect of this new (indistinct). And of course, Dell Technologies is with us in this transition. >> I loved how you described your data centers as a Dell Technologies supermarket. Maybe a different way of talking about a center of excellence. Kaushik, I want to ask you about... I know that the University of Pisa is a 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, like Maurizio has talked about, has a lot of the Dell products today. And in fact, he mentioned about the powered servers, the Power Scale F 900 is actually based on a powered server. So you can see. So a lot of these technologies are sort of interlinked with each other. They talk to each other, they work together and that sort of helps customers manage their entire ecosystem life cycle, data life cycle together versus as piece spots, because we have solutions that solve all aspects of our customer, like Maurizio's needs, right? So, yeah, I'm glad Maurizio is leveraging Dell and I'm happy we are able to help Maurizio solve all his use cases and when. >> Lisa: Excellent. Maurizio, 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? >> The leaning tower is an engineering miracle. Some years ago, an incredible engineering worker was able to fix the leaning for a while, and let's hope that the tower of Pisa stay there because it's one of our beauty that you can come to visit. >> And that's one part of Italy I haven't been to. So post pandemic, I got to add that to my travel plans. Maurizio 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. >> Kaushik: Thank you. >> Maurizio: Thank you. For my guests, I'm Lisa Martin. You're watching theCUBE's coverage of Dell technologies world, the digital event experience. (upbeat music)