>> Hi. I'm Peter Burris and welcome to another Cube Conversation. We're here in our Palo Alto studios and we got some really interesting guests, really interesting topic. We're going to talk about something called Computational Storage. Nader Salessi is the CEO of NGD Systems. >> Hello. >> And Scott Shadley is the VP of Marketing of NGD Systems. >> Pleasure to see ya again, Peter. >> So guys, let me set the stage and let's get in to this 'cause actually this is kind of interesting. If you think about a lot of the innovations happening in the marketplace right now and 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 I/O aggregate required but the presumption behind all this is that we're going to be flying data all over the organization and the other presumption is 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 a dressing. Nader, 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 distributive fashion as you have number of storage devices in a server without the need of moving the data and save energy. The main area is that it's a focus point for a lot of mega-data centers is the energy density being what per terabyte or what per terabyte per square inch and that's exactly with our technology we are addressing to have a more sufficient energy efficient computational storage into the market. >> So let me build on that a little bit. 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, 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 35, 40 watts off the card, you're doing it for-- >> A fraction of that so we'll be able to do that with eight terabytes in an eight watt envelope. Or 64 terabytes to be done in a 15 watt envelope. That's the part that doesn't exist today and being able to not only 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 levels of the application is what market is looking for that doesn't exist today. >> So you're using, 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 standpoint? >> Very good question. So we are using a standard PCIe and MPE protocol for the drive. So we, our technology, the algorithm and the controller technology can have this large capacity of the NAND and we are flash agnostic so it could be any NAND, in fact, later on it could be any MBM. It doesn't need to be the NAND and having additional resources through the standard of the TCP/IP we can bring application down. We're not making any changes to the application. >> So we're taking a new approach to thinking about how I/O gets handled at the storage device. It's got to create some use cases, Scott. Tell us about some of the use cases. >> From a use cases perspective, you can think about it you can go to simple terms as thinking about traffic jams. If you have a traffic jam on the freeway when one 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 and memory, tie up CPU resources, you just tell the drive go find this picture. It goes, finds this comparison 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 I/O 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 'cause you have to 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 Floier, has been talking about how for example MAP and Hadoop could be accelerated pretty dramatically. But it's got to be more than just MAP? How are you supporting a range of applications. >> The of use cases totally separate, different from these use cases is for the content delivery, video delivery on the last mile or last hundred feet. So today, everybody's recording at home in their DVRs. What if it's set up having 10,000 DVRs in 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. With all our technology, we can do the encryption on the way out and authentication right at the storage so the concurrent users can be protected from each other. And that technology doesn't exist. >> Let me think about the business model implications now 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 presense 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 there 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 MVE was going to be the savior of the world. It comes in at flash storage. It gives you the unlimited PCA bandwidth bus. The problem is we've already saturated that problem. We've got devices where a box can hold 24 MVE drives but you can only operate three or four of them at a time even with 16 lanes of PC-83. We're going to PC-84. We've still got a bottleneck because all of the I/O still has to go from the 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 it's 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 at a random access pattern. >> So that brings us back to the question I asked earlier. Namely, to make this more general purpose, there's got to be a pretty robust software capabilities or libraries. How is that being handled so it can be made more general purpose and folks aren't building deep into the architectures specific controller elements. How is that happening? How does it work? >> So one of the biggest kricks 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? 'Cause I want ease. I want to do simple. It took forever to get people to adopt SSDs and now we're telling them that we're giving them 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 MVE 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 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 of enterprises of all sorts are actually trying to drive, that are more data orientated, computational orientated around that data. Get the computations closer. You guys are helping. From the new systems designs, we still think MVEOF is going to be very, very important but this could complement it. >> Exactly. >> Especially where I/O and the energy that bus becomes a crucial issue. What's on the horizon? >> Deploying this and driving the energy deficiency. 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 server and computer that's being deployed and that's another area that we are focusing on and continue to focus to have the most optimum energy efficient in the smallest footprint in the model. >> 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. Before that, myself as well as my two co-founders as well as a team of engineers we used to be at a company called Western Digital for a couple of years doing enterprise classes as this. Before that, I started the, in 2003, in this field for SSD, I started a product, a business line for a company called SDC Estate which we created industrial SSDs then later on became an enterprise class SSD. We became known for enterprise class SSDs in the industry. That's the heritage of the last 15, 17 years with many years of SSD development but this computational storage is already done 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 really didn't 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 a CPU, GPU or otherwise and actually being able to use intelligent storage to drive the bandwidth growth, the MVE fabric, or just the per-box density is just something that nobody's really taken a significant look at in the past. This is a definite solution to move it forward. >> So I'm going to turn that around and say software developers always find a way to fill up the space. So you can on the one hand look at it from a maybe you have low-cost CPUs but even if you have the same cost CPUs you can do so much more 'cause you can move so much more work out closer to the data. >> Correct. = All right. NGD Systems. Very, very interesting conversation. Thanks so much for coming and being on Cube. Once again, this is Peter Burris with a Cube Conversation. We've been speaking with NGD Systems. Thanks a lot for watching.