The first business computers were huge contraptions that took up rooms. Technology advanced, and computers became boxes that sat on a desk or in a rack. Now, the confluence of artificial intelligence, 5G networks that enable the internet of things, and super-powerful processors is forcing computers out of the box once more.

“The new unit of computing is really the data center,” said Kevin Deierling (pictured, right), senior vice president of marketing at Nvidia Corp. “That’s the scale of the types of problems we’re solving.”

Deierling and Paresh Kharya (pictured, left), director of product management for data center and cloud computing, at Nvidia, spoke with Stu Miniman, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during the HPE Discover Virtual Experience event. They discussed the BlueField programmable data processing unit and the evolution of data processing, advances in AI, and Nvidia’s partnership with Hewlett Packard Enterprise Co. (* Disclosure below.)

[Editor’s note: The following content has been edited for clarity]

AI is obviously a mega trend. Can you describe where Nvidia sits and what the market is?

Kharya: We are witnessing a mass of changes that are happening across every industry, and it’s from the confluence of three things: One is of course, AI; the second is 5G and the IoT; and the third is the ability to process all of the data that we have.

In AI we are seeing really advanced models, from computer vision to understanding natural language to the ability to speak in conversational terms. In terms of IoT and 5G, there are billions of devices that are sensing and inferring information, and now we have the ability to act, make decisions in various industries. And, finally, with all of the processing capabilities that we have today, at the data center, and in the cloud, as well as at the edge with the GPUs as well as advanced networking that’s available, we can now make sense all of this data to help industrial transformation.

When you look at some of these waves of technology, there are a lot of new pieces, but architecturally some of these things remind us of the past. Can you say what’s the same and what’s different about this highly distributed, edge compute, AI, IoT environment?

Deierling: When you move to the edge, instead of having a single data center with 10,000 computers, you have 10,000 data centers, each of which has a small number of servers that is processing all of that information that’s coming in. But in a sense, the problems are very, very similar whether you’re at the edge or you’re doing massive high-performance computing, scientific computing, or cloud computing. And so we’re excited to be part of bringing together the AI and the networking, because they are really optimizing at the data-center scale across the entire stack.

So, obviously, we know CPU’s. When we think about GPUs, we think of Nvidia. Google came out with Cloud Tensor Processing Units. But what are the data processing units Nvidia just announced? Is this just some new AI thing or a new architectural model? 

Deierling: There are three key elements of this accelerated disaggregated infrastructure that the data center is becoming. One is the CPU, which is doing traditional single-threaded workloads. But for all of the accelerated workloads, you need the GPU. And that does massive parallelism, deals with massive amounts of data. But to get that data into the GPU and also into the CPU, you need an intelligent data processing unit because of the scale and scope of GPUs and CPUs today. These are not single core entities; these are hundreds or even thousands of cores in a big system. So you need to steer the traffic exactly to the right place, and you need to do it securely, you need to do it virtualized, you need to do it with containers.

To do all of that you need a programmable data processing unit. So we have something called our BlueField DPU, which combines our latest, greatest, 100Gb/s and 200Gb/s network connectivity with ARM processors and a whole bunch of accelerators for security, for virtualization, for storage. And all of those things then feed these giant parallel engines, which are the GPU, and of course the CPU, which is really the workload at the application layer.

Could you expand on the implications of AI at the edge?

Kharya: AI is basically not just one workload. AI is many different types of models, and AI also means training as well as inferences, which are very different workloads. So on one hand we are seeing the size of the AI models increasing tremendously, and in order to train these models, you need to look at computing at the scale of data center, many processors, many different servers working together to train a single model. On the other hand … applications are being powered by AI, and each application requires a small amount of acceleration. So you need the ability to scale out and support many different applications.

So with our newly launched Ampere architecture that was announced by Nvidia founder and Chief Executive Officer Jensen Huang just a couple of weeks ago, we are now able to provide both scale up and scale out, both training data analytics as well as imprints on the single architecture.

Deierling: The other thing that’s interesting is you’re talking about at the edge and scale out versus scale up. The networking is critical for both of those, and there’s a lot of different workloads, as Paresh was describing. You’ve got different workloads that require different amounts of GPU or storage or networking.

So, part of that vision of this data center as the computer is that the DPU lets you scale independently everything. You desegregate into DPUs and storage and CPUs, and then you compose exactly the computer that you need on the fly, containerized, to solve the problem that you have right now. So, the new way of programming is programming the entire data center at once; and you’ll go grab all of it, and it’ll run for a few hundred milliseconds even. And then it’ll come back down and recompose itself onsite.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the HPE Discover Virtual Experience event. (* Disclosure: TheCUBE is a paid media partner for the HPE Discover Virtual Experience. Neither Hewlett Packard Enterprise Co., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE