GPUs: Explained

hi my name is alex hudak i'm an offering manager at ibm and today i'm going to talk to you about what is a gpu so i get some pretty basic questions on gpus and that's what i'm going to go over today first question is what is a gpu what is the difference between a gpu and a cpu so i'm going to represent those here and then lastly why use a gpu and is it even important to use a gpu on cloud so let's start first with what is a gpu gpu stands for graphic processing unit but oftentimes people are more familiar with cpus so cpus are actually made up of just a few cores you can think of these cores as the power or the ability of a cpu to do certain calculations or computations on the other hand though gpus are made up of hundreds of cores but what difference does it make so the thing with a cpu is that when it does the computation it does so in a serial form so it does one computation at a time but with the gpu it does it in parallel so the importance of these two differences is that with a gpu you're able to do computations all at once and very intense computations at that so oftentimes when you have app codes a lot of it's going to be going to the cpu but then every now and then you're going to have an application that's going to require quite a bit of compute intensive support that the cpu just can't do so it's going to be offloaded to the gpu so you can think of a gpu as that extra muscle or that extra brain power that the cpu just can't do on its own so there are two main providers of gpus in industry nvidia and amd both providers manufacture gpus that are optimized for certain use cases so let's jump into that because big question i get is why do i even need a gpu in what industries and in what use cases so the first we'll talk about is vdi vdi stands for virtual desktop infrastructure so gpus are created to support high intensive graphic applications so for think about if you're a construction worker right and you're out in the field and you need to access a very high graphic intensive 3d cad program so rather than having the server right next to you right in the field with you you can have a server that's in a country away in a cloud data center and be able to view that 3d graphic as if that server was right with you and that's going to be supported by the gpu because the gpu supports graphic intensive applications another example of this would be movie animation or rendering so in fact gpus actually first got their name mainly with the gaming industry oftentimes they were referred to as gaming processing units because of this ability to provide end users with low latency graphics but gaming is no longer the focus in industry anymore it's big piece of it but now financial services life sciences and even healthcare are starting to get into it with artificial intelligence so artificial intelligence has two big pieces to it there's machine learning and there's deep learning so now there are also gpus that are optimized and created specifically for those applications so there are some that are created for inferencing for machine learning purposes and there are some that are created to help data scientists create and train neural networks in other words they're trying to create these algorithms that can think like a human brain that's something that a cpu can simply not do on its own and requires gpu capabilities and then lastly let's talk about hpc hpc is a buzzword that's been going around it stands for high performance computing while a gpu is not absolutely necessary for hpc it's an important part of it so high performance computing is the company's ability to spread out their compute intensive workloads amongst multiple compute nodes or in the case of cloud servers oftentimes though these applications are very compute intensive it could include rendering it could include ai and that's where a gpu comes in you can add a gpu to these servers that are spread out amongst an hpc application and utilize those in that manner so this is a nice little segue into why should we use gpus on cloud if hpc is such a big piece of that what else is important about cloud so the first part of that is you get high performance you need cloud for that the gpus are great but not on their own so back in the day and even still today there are companies that use a lot of on-prem infrastructure and they utilize that infrastructure for any of their compute intensive applications however especially in the case of gpus the technology is ever changing in fact there's typically a new gpu coming out almost every single year so it's actually very expensive and nearly impractical for companies to keep up with the latest technology at this point so cloud providers actually have the ability to continually update their technology and provide gpus to these companies to utilize them when they need them so on a more granular basis though cloud technology can often be broken down from an infrastructure perspective between bare metal and virtual servers so let's talk about the differences there are advantages of using a gpu on both types of infrastructure if you utilize a gpu on a bare metal infrastructure the companies oftentimes have access to the entire server itself and they can customize the configuration so this is great for companies that are going to be really utilizing that server and that gpu intense application on a pretty consistent basis but for companies that need a gpu maybe just in a burst workload scenario the virtual server option might be even better and the nice thing about virtual is that there are often different pricing models as well including hourly and the cool thing about cloud is that you only pay for what you use so if a company is using on-prem technology or infrastructure but they're not utilizing it at the time that technology is depreciating and it's essentially a waste of money for that company so it just makes a lot more sense from a cost perspective and then because the gpu is so great at performance it just makes sense from a performance perspective as well so companies are able to focus way more on output than they are on keeping up with the latest technology so in summary what we covered is what is a gpu graphic processing unit what the differences between a gpu and a cpu the use cases for gpus being in vdi ai and hpc and why is it even important for gpus to be used on cloud thank you guys for joining me here today to learn about what is a gpu if you'd like to learn more about gpus click on the links below and we're always checking the comments so feel free to throw one in there for us and be sure to subscribe for future videos

Channel: IBM Technology

Views: 302,366

Keywords: gpu, cpu, graphic processing unit, cores, serial computation, parallel computation, compute-intensive workload, nvidia, amd, vdi, virtual desktop infrastructure, graphic-intensive, 3d cad, animation, rendering, gaming, gamin processing unit, graphics, artificial intelligence, ai, financial services, life sciences, healthcare, machine learning, deep learning, neural network, hpc, high performance computing, cloud, bare metal, virtual servers, infrastructure

Id: LfdK-v0SbGI

Length: 7min 29sec (449 seconds)

Published: Wed Mar 20 2019