 I'm Peter Burris and welcome to another CUBE conversation. We're here in our Palo Alto studios. We've got some really interesting guests, really interesting topic. We're going to talk about something called computational storage. And Nate or Celesi is the CEO of NGD Systems. Hello. And Scott Shadley is the VP of marketing of NGD Systems. How's your seeing him here? So guys, let me set the stage and let's get into this because this actually is kind of interesting. If you think about a lot of the innovations happening in the marketplace right now in the tech industry right now. We're talking about greater densities of data, more advanced algorithms being applied against that data, greater parallelism in the compute, more IO aggregate required. But the presumption behind all of this is that we're going to be flying data all over the organization. And the other presumption is that things like energy consumption, unlimited. Who cares? But we know the reality is something different. There is an intersection amongst all of that that seems to need addressing. Nate, take us through that. And that's exactly what we are addressing. So we are bringing other than the energy efficiency in a large capacity storage. Instead of moving the data to do any computation on the data, we bring the computation inside the storage to do the computation locally in a distributed fashion as you have a number of storage devices in a server. And without the need of moving the data and save energy. The main areas that it's a focus point for a lot of mega data centers is the energy density being watt per terabyte or watt per terabyte per square inch. And that's exactly with our technology we are addressing to have a most efficient energy efficient computational storage into the market. So let me build on that a little bit and see if I got it. So that your traditional large system, you have an enormous amount of data, you have a bunch of logic dedicated to know where the data is, find it. Once it finds it, it brings it and presents it to a CPU, a server somewhere who then takes some degree of responsibility for formatting it and then presenting it to the application. And you're bringing that out and putting it down closer to the storage itself. And so instead of having this enormous bus that's humming along at unbelievable speeds and maybe a 35, 40 watts off the card, you're doing it for. For a fraction of that. So we'll be able to do that with eight terabytes in a eight watt envelope or 64 terabytes to be done in the 15 watt envelope. That's the part that it doesn't exist today. And being able to not only to do the storage part of it, but bringing the application seamlessly without changing the application, bringing it down and acting on the data and just setting the subset of the results to the upper level of the application is what market is looking for that doesn't exist today. So you're still using industry standard memory, you're still using industry standard form factors. What is the special sauce inside this that makes it faster and cheaper from a power stamp? Very good question. So we are using a standard PCIe NVMe protocol for the drive. So with our technology and algorithm and the controller technology, we can address large capacity of the NAND and we are flash agnostic. So it could be any NAND. In fact, later on it could be any NVM. It doesn't need to be NAND. And having additional resources that through the standard of the TCPIP, we can bring application down without making any changes to the application. So we're taking a new approach to thinking about how IO gets handled at the storage device. Scott, it creates some use cases. Scott, tell us a little bit about some of the use cases. Yeah, so from a use cases perspective, you can think about it. If you want to do, you can go as simple terms as thinking about traffic gems. If you have a traffic gem on the freeway when lane of traffic gets stuck, well, if the cars are able to actually relocate and do the movements on their own, you eliminate the traffic bandwidth problem. What we can do is we allow you to say, okay, if I'm going to go look for a picture in a data set, instead of having the CPU ask for all the different pictures, do the comparison in memory, tie up CPU resources, you just tell the drive, go find this picture, it goes finds, compares the picture, tells you all about the picture, sends just that little tidbit back to you. So if you're collecting hundreds of thousands of Facebook photos today, you can analyze those and tell every person that's looking for a different photo, what their photo is, without having to use massive IO bandwidth. So traditional high performance computing? Yes. IoT? IoT, all of the AI where you're looking for things where you're trying to have artificial intelligence be smarter, you have to throw CPUs and GPUs at it, start throwing more storage at it because you have to store all the data you're generating. Why not let the storage do some of that work? You can offload some of it from CPUs, GPUs and you can scale more effectively. So my colleague, David Froyer, has been talking about how, for example, map in Hadoop could be accelerated pretty dramatically, but it's got to be more than just map. How are you supporting a range of application forms? Another use case totally different from these use cases is for the content delivery, video delivery on the last mile or last 100 feet. So today everybody is recording at home in their DVR. What if instead of having 10,000 DVRs and 10,000 homes is sitting in a central place and it has hundreds of thousands of video, but everybody points to it. The new challenge with that is the security portion of it. With our technology, we can do the encryption on the way out and the authentication right at the storage. So the concurrent users can be protected from each other. So let me think about the business model implications of that for a second. So I might enter as a private citizen, I might enter into a deal with Xfinity, for example, in which I agree to be the point of presence for my entire neighborhood. Is it that kind of thing we're talking about? Exactly, so that's the new edge delivery, but with a higher security that doesn't exist today. Because it's a major challenge for everybody. Interesting. For the security and authentication. Even within the same household, it could be multiple users that they need to be protected from each other. Very interesting. So Scott, you've got a fair amount of background in the systems universe. How is this technology going to change the way we think about systems? Yeah, so the beauty of this is we all thought NVMe was going to be the savior of the world. It comes in at flash storage. It gives you the unlimited PCIe bandwidth bus. The problem is we've already saturated that problem. We've got devices where a box can hold 24 NVMe drives, but you can only operate three or four of them at a time, even with 16 lanes of PCIe three. We're going to PCIe four. We've still got a bottleneck because all of the IO still has to go from drive to host and back to drive and be managed because you can't run on traditional storage, anything other than just data placement. Now the drives are smart. They're relocating the data on it, protecting it, whatever else, but they're still not doing what can really be done with them. Adding this layer of computational storage with devices like ours, all it has to do is go ask the question and the storage can go do its thing. So if I've got 24 drives, I can go ask 24 questions and I still have bandwidth to actually write data into that system or read other data out of that system and a random access pattern. So that brings us back to the question I asked earlier that namely that to make this more general purpose, there's got to be a pretty robust software capability or a set of libraries. How is that being handled so that it can be made more general purpose and folks aren't building deep into the architecture specific controller elements. How's that happening? How's it working? So one of the biggest tricks whenever you bring something kind of new and innovative that actually solves a problem that does exist is how to get people to address it, right? Because I want ease. I want to do simple. It took forever to get people to adopt SSDs. Now we're telling them we're going to have smart SSDs. What we're saying and what we're able to accomplish with what we're doing on the library front is very light touch. We're using the NVMe protocol. We're tunneling through it with a host agent which is a very small modification at the host and it has that now communicate to all the different drives. So simplifying that crossover of information is really what's important to your exact statement and we do that through a C library and it's very modifiable to various different workloads. It's not tied to each workload has to be independently written. So the applications and enterprises of all sorts are actually trying to drive that are more data oriented, computational oriented around that data to get the computations closer. You guys are helping for the new systems designs. We still think NVMeOF is going to be very, very important but this can complement it. Exactly. Especially where the, where IO and the energy that thus becomes a crucial issue. What's on the horizon? Well, deploying this and driving the energy efficiency. It continues to be the biggest point no matter what we do, there is not enough energy in the world with the amount of storage and the server and compute that is being deployed. And that's another area that we are focusing and we continue to focus to have the most optimum energy efficient in the smallest footprint in the marketplace. So I got one more question. NGD Systems is not a household name. Where are you guys from? So we started the company about five years ago. We, before that, myself as well as my two co-founders as well as a team of engineers. We used to be a company called Western Digital for a couple of years doing enterprise class SSDs. And before that, I started in 2003 in this field for the SSD. I started a product business line for a company called STC-STEC, which we created industrial SSDs and then later on became an enterprise class SSD. We became known for enterprise class SSDs in the industry. Yeah, and that's our heritage of last 15, 17 years with many years of SSD development, but this computational storage is other than doing an optimized SSD for a category that doesn't exist today and add to it a computational storage capability on top of it. Scott, last word. Yeah, just from that perspective, we didn't really get into a lot of detail on it, but the capabilities of reducing the amount of compute you need in a server, whether it be CPU, GPU or otherwise, and actually being able to use intelligent storage to drive the bandwidth growth, the NVMe over fabric or just the per box density is just something that nobody's really taken a significant look at in the past, and this is a definite solution to move it forward. So I'm going to turn it around slightly and say, software developers always find a way to fill up the space. So you can, on the one hand, look at it from maybe have low cost CPUs, but even if you have the same cost CPUs, you can do so much more because you can move so much more work out closer to the data. Correct, that's right. Great. All right, NGD Systems, very, very interesting conversation. Thanks very much for coming in and being at CUBE. Once again, this is Peter Burris with theCUBE Conversation. We've been speaking with NGD Systems. Thanks a lot for watching. Thank you, appreciate it.