[Music] and welcome back everybody Jeff Rick here at the cube we're in Austin Texas at the deli MC high performance computing and artificial intelligence labs last been here for a long time as you can see behind us and probably here racks and racks and racks of some of the biggest baddest computers on the planet in fact I think number 256 we were told earlier it's just behind us we're excited to be here really as Dell and EMC puts together you know pre-configured solutions for artificial intelligence machine learning deep learning applications because that's a growing growing concern and growing growing importance to all the business people out there so we're excited to have the guy running the show he's Terry Pellegrino the VP of HPC and business strategy had a whole bunch of stuff you're a pretty busy guy I'm busy but you can see all those servers they're very busy too they're humming so just your perspective so the HPC part of this has been around for a while the rise of kind of machine learning and artificial intelligence as a business priority is relatively recent but you guys are jumping in with both feet oh absolutely I mean HPC is not new to us AI machine learning deep learning is happening that's the buzzword but we've been working on HPC clusters since back in the 90s and it's it's great to see this technology or this best practice getting into the enterprise space where data scientists need help and instead of looking for a one processor that will solve it all they look for the knowledge of HPC and what we've been able to put together and applying into their field right so how do you kind of delineate between HPC and say the AI portion of the lab or is it just kind of on a on a continuum how do you kind of slice and dice absolutely it's it's all in one place and you see it all behind us this area in front of us we try to get all those those those servers put together and add the value for all the different workloads right so you get HPC a piece equal a IML deal all in one lab right and they're all here they're all here the old the legacy application only be called legacy applications all the way to the to the meanest and the newest and greatest exactly the old stuff the new stuff and and actually you know what some things you don't see is we're also looking at where the technology is going to take all those workloads AI m LD L is the buzzword today but down the road you're gonna see more applications and we're already starting to test those technologies in this lab so it's past present and future right so one of the specific solutions you guys have put together is the DL using the new Nvidia technology what if you could talk we hear about a media all the time obviously they're in really well position in autonomous vehicles and and their GPUs are taking data centers by storm how's that going where do you see some of the applications outside of autonomous vehicles for the the Nvidia base oh there are many applications I think the technology itself is is proving to solve a lot of customer problems and you can apply it in many different verticals many workloads again and you can see it in autonomous vehicles you can see it in healthcare live science in financial services risk management it's it's really everywhere you need to solve a problem and you need dense compute solutions and NVIDIA has one of technologies that a lot of our customers leverage to solve their problems right and you're also launching a machine learning solution based on Hadoop which we we've been going to Hadoop summit Hadoop world and strata for eight nine years I guess since 2010 eight years and you know it's kind of funny because the knock on Hadoop is always there aren't enough people it's too hard you know it's just a really difficult technology so you guys are really taken again a solutions approach with a dupe for machine learning to basically deliver either a whole rack full of stuff or that spec that you can build at your own place no absolutely that's one of the three major tenants that we have for those solutions that we're launching we really want it to be a solution that's faster so performance is key when you're trying to extract data and insights from from your data set you really need to be fast you don't want it to take months it has to be within countable measures so it's one of them we want to make it simple a data scientist is never going to be a PhD in HPC or any kind of computer technologies so making it simple it's critical and the last one is we want to have this proven trusted adviser feel for our customers you see it around you this HPC lab was not built yesterday it's been here showcasing our capabilities in HPC world our ability to combine the Hadoop environment with other environments to solve enterprise class problems and bring business value to our customers and that's really what we we think are our differentiation comes from right and it's really a lab I mean you and I are both wearing court coats right now but there's a gear stack following really heights of every shape and size and I think what's interesting is while we talk about the sexy stuff the GPUs and the CPUs and the do there's a lot of details that make one of these racks actually work and it's probably integrating some of those things as lower tier things and making sure they all work seamlessly together so you don't get some nasty bottleneck on an inexpensive part that's holding back all that capacity oh absolutely you know it's funny you mentioned that we're talking to customers about the technologies we're assembling and contrary to some web tech type companies that just look for any compute at all costs and they'll just stack up a lot of technologies because they want the compute in in HPC type environments or when you try to solve problems with deep learning and machine learning you're only as strong as your weakest link and if you have a a server or a storage unit or a an interconnect between all those that is really weak you're gonna see your performance go way down and we watch out for that and you know the one thing that you alluded to which I just wanted to point out what you see behind us is the hardware the the secret sauce is really in the aggregation of all the components and all the software stacks because AI M LDL great easy acronyms but when you start peeling the layers you realize it's layers and layers of software which are moving very fast where you don't want to be spending your life understanding the inter up requirements between those layers and and worrying about whether your your compute and your storage solution is gonna work right you want to solve problems a scientist and that's what we're trying to do give you a solution which is an infrastructure plus a stack that's been validated proven and you can really get to work right and even within that validated design for a particular workload customers have an opportunity maybe needs a little bit more IO as a relative scale these a little bit more storage needs a little bit more compute so even within a basic structured system that you guys have SPECT and certified still customers can come in and make little mods based on what their specific workload you've got it this is not we're not in the phase in the acceptance of a I am LDL where things are cookie cutter it's still going to be a collaboration that's what we have a really strong team working with our customers directly and trying to solution for their problem right if you need a little bit more storage if you need faster storage for your scratch if you need a little bit more i/o bandwidth because you're in a remote environment I mean all those characteristics are gonna be critical and the solutions we're launching are not rigid they're they're perfect starting point for customers I want to get something to run directly they feel like it but if you if you have a solution that's more pointed we can definitely iterate and that's what our team in the field and all the engineers that you have seen today walk through the lab that's what their role is we want to be as a consultant as a partner designing the right solution for the customer right so Terry before I let you guys just kind of one question from your perspective of customers and you're out talking to customers and how the conversation around artificial intelligence and machine learning has evolved over the last several years from you know kind of a cool science experiment or it's all the HPC stuff with the government or whether or heavy lifting really moving from that actually into a boardroom conversation as a priority and a strategic imperative going forward how's that conversation evolving when you're out talking to customers well you know it has changed you're right back in the 60s the science was there the technology wasn't there today we have the science we have the technology and we're seeing all the C Class decision makers really want to find value out of the data that we've collected and that that's where the discussion takes place this is not a CIO discussion most of the time and in what's really fantastic in mama contrary to a lot of the the technologies I have grown on like big data cloud and all those buzzwords here we're looking at something that's tangible we have real-life examples of companies that are using deep learning and machine learning to solve problems save lives and get our technology in the hands of the right folks so they can impact the community it's really really fantastic and that growth is set for success and we want to be part of that right it's just a minute just you know the continuation of this democratization trend you know get more people more data give more people more tools get more people more power and you're gonna get innovation you're gonna solve more problems and it's so exciting absolutely totally agree with you all right teri well thanks for taking a few minutes out of your busy day and congrats on the Innovation Lab here thank you so much all righty teri I'm Jeff Rick we're at the Dell EMC HPC and AI innovation labs in Austin Texas thanks for watching