Nader Salessi and Scott Shadley, NGD Systems | CUBEConversation, August 2018
(energetic music) >> Hi, I'm Peter Burroughs and welcome to another CUBEConversation from our wonderful studios in Palo Alto, California. Today we're talking storage, not just any kind of storage, but fast, intelligent storage. We're got NGD Systems with us, and specifically welcome back to theCUBE, Nader Salessi, CEO founder, and Scott Shadley, VP of Marketing. >> Good to see you again, Peter. >> So, the last time we were here we had a great conversation about the role that storage is going to play in overall system performance. And Nader, when I think of NGD Systems, I think of really smart people doing great engineering to create really fast high-performance products. Where are we in the state of the art of fast storage, fast systems? >> So, what we are learning from the customers, the demand of the storage continues to grow exponentially. They want larger capacity per drive. All the challenge they have, physical space is limited always and the power consumption. It is not necessarily just power consumption of the device, they have also self resources for implementing their Hyperscale Data Centers from the physical space, from buying servers, network storage. The challenge that they face is power available from the utility companies are limited. They cannot overcome that. So, if they need to increase their capacity of the storage by double the size of the storage in a year timeframe, they cannot get access to the utilities and the power. So, they need to focus on energy efficiency. >> So, when I think of NGD Systems, what I should think about is smart, fast, and efficient from a power standpoint. >> That's correct. So, that's one of the areas that we are focusing a lot to provide energy efficient. We are improving the watt per terabyte by a factor of 10 compared to the best in class available the other side of the SSD drive that exists in the industry. >> Oh, let me make sure I got that. So, by improved wattage by a factor of 10 for the same capacity. >> Correct. In meaning we are improving watts per terabyte in a same physical space. And that's the challenge that the industry is facing. >> Got it. >> The next set of the challenge that all the hyperscalers are facing, and we are learning from them, moving of the data is a challenge. It just takes time and it's not efficient. So, the more they can do inside of the drive to do the manipulation of the data without moving the data, that's what they are looking for. And that's exactly where we are focusing and with our intelligent product that we're introducing. In the fourth quarter of this year, we are introducing mass producible solution that can take it to a mass production. >> So, give us an example of that, 'cause I know you were one of the first suppliers of technology that did things like brought mass produced down closer to the data. Is that the basic notion that we're talking here, and what are the use cases we're looking at? >> So, there are by far a lot more use cases and I'll let Scott go into some of the use cases that we have implemented as an example with some large partners which we are also announcing this coming week, or next week during the FMS. So, Scott, do you want to explore? >> Yeah, absolutely, so Peter, just to give to your point. There's a lot of different ways you can look at making storage intelligent. What we looked at we took a different direction. We're not trying to just do simple things like the minor database applications, we're going for what's new and innovative in the way of things like AI and machine learning. So, we talked last time a little bit about this image similarity search concept. As Nader mentioned, we're going to be live with a guest speaker at FMS implementing a version of that. >> Now, FMS is Flash Memory Summit. >> Yes, for those that don't know, Flash Memory Summit that happens every year. Other things that we've worked on again with partners relate to things like relational databases and being able to do things like implement Google TensorFlow live in the drive. We've also been able to port docker containers directly into the drives, so then there's now a customer's ability to take any application you're running, whatever format it's in and literally drop it in a container format into the drive and execute the commands in place on the data. And we're seeing improvements of 10 to 50x on execution time of those applications because they're not physically moving data around. >> So, to put this, kind of summarize this, if a customer, user, has a choice of moving 50 terabytes around of raw data as opposed to moving maybe a couple of hundred kilobytes or megabytes of application down to the drive, then obviously you want to move the smaller down. But it requires a fair amount of processing power and control be located very close to the data. So, how's that happening? >> So, by architecting the fundamentals of the storage from a sketch, we are able to provide the right solution. So, architecting within each control, or each SSD there is a controller for managing the flash and the interfacing with the host. As part of that, we have embedded additional resources. Part of it is a quad-core application processor, 64 bit application processor that is running at at least a gigahertz that the application can come down and run on that, or operating system is running on it. In addition to that we have embedded the hardware accelerator to accelerate certain functions that makes sense to be done. Plus the access to the data tower that is readily available at a much higher bandwidth than the host interface. So, that's how we are at this end. Then of course, by providing the complete software stack to make it easy for the customers to bring their application rather than starting from scratch, or having it very specialized and custom solutions. >> So, when I think about if I'm a CIO or if I'm a senior person in infrastructure, I'm thinking, what workloads naturally lend themselves to high degrees of parallelism? Then I'm thinking, how can I move more of that parallelism closer to the data. Have I got that right? >> Exactly. >> Absolutely. >> So, how's this turning into product? >> So, for that perspective we've been releasing, or we've had released now two platforms we've called the Catalina Family of Solutions. And they've been POCs, prototypes, and some limited production volume. As Nadir mentioned, our third platform we're calling the Newport Platform is going to be an ASIC base solution that's going to be able to drive that mass marketed option that he referenced. It's a whole bunch of unique things about it. A, we have the application coprocessors. It's the first SSD controller to ever be done on a 14 nanometer process node, so that's where the energy efficiency piece of this comes into play. And the fact that we can do the densities the customers are looking for. 'Cause right now, there's a challenge in the market to be able to do a large enough drive at the right performance characteristics and power consumption to solve the need. >> So, you're following some locations in Southern California, from Catalina to Newport. In the next couple of years you'll be in the San Bernardino Mountains. >> Sure. >> So, as we think about where the technology is, so give us an example of the performance improvements, which you're seeing from an overall benchmark standpoint. >> So, one of the other use cases that it may not be intuitive to think about this is for the content of a video, for video content everywhere. So, the new generation of contents, they are large, they are massive, they require massive amounts of storage. And the old fashioned way of doing it, they have multiple drives in a server. They all converge and they go through another server for the encryption and authentication. Well, we are moving that function inside of the storage. Now, all of a sudden, same server instead of having all converging and going through one narrow pipe, all the drives concurrently can serve multiple subscriber in parallel by more than factor of 10. And that's substantial from the performance point of view. So, it is not necessary the old fashioned way of measuring it, what's the IOPS, those are the old way of measuring it. The new ways, the end users how they can access the data without being a bottleneck. And that's again, another use case of it. The other use case as Scott mentioned for the doing image similarity search, in the old fashioned way when they were accessing a billion images, it's working fine with the current SSDs, off the shelf SSDs, and the current servers, and GPUs. The challenge they are facing as they increase this database to a trillion images, it just cannot do it that old way. So, it's more than just how many gigabytes they push through or how many IOPS. It's being able to look at it from the system level point of view, and how many subscribers or how many customers can access it concurrent. >> So, you're describing a number of relatively specialized types of applications, but nonetheless, applications of significant value to their businesses. But let's talk just for a second about how a customer would employ the technology. Customers don't mind specialized or more specialized devices as long as they fit in within the conventions for how they get used. So, what's the complexity of introducing your product? >> Very good point that you're raising. Fundamentally, we are a solid state drive storage as a block storage based on PCle NVMe without any drivers. They plug it in, it's plug and play. It works. On top of that, and for this scenario of the block storage, we are the highest capacity, lowest power consumption, or lowest watt per terabytes, and servicing the majority of the market that nowadays are focused more on the read and consistent read, rather than what's the again, IOPS or how fast is the write. So, we have our architecture and the algorithms is set up that we would provide a very narrow beam of the consistent latency no matter what workload they put on it, and provide the right solution for them. Then on top of that, if they have a specialized workload or the use cases, they still can enable it or disable it based on simple software switch. >> So, Scott, when you think about partners, the ecosystem, I know that we talked about this a bit last time, getting started, expanding it, where are we in terms of NGD Systems getting the market? >> Absolutely, so from that perspective we've gone beyond the proof of concept only phase. We've actually got production orders that have shipped to customers. We're starting to see that roll out in the back half of this quarter. As Nadir mentioned, we roll into Q4 with the new product, then upgrade those customers and start getting into even larger rollouts. But it's not just a couple of mom and pop shops type of thing. It's some big names. It's some high-level partners. And we're starting to now build out the ecosystem and how to deliver it through server ODMs or other partners that can play off of the system, whether it be storage array providers or even some of the big box players. >> So, we're now here with Newport. >> Yes. >> You've no doubt got plans. We don't have to go too deep into 'em, but as your company starts to scale, what's the cadence going to look like? Are you going to be able to continue to push the state of the art from performance smarts and energy efficiency standpoint? >> Absolutely, there are already things that are in the pipeline for the next generation of how to bring more intelligence inside of the drive. With more resources for a lot more workload to be able to adapt itself to many, many use cases, rather than only maybe today it might be a dozen use cases, to go infinite. It truly is a platform rather than just a unique for this application. And then we're going to expand on that toward the next generation of it. So obviously, as we ramp up the first generation of product in mass production, the R&D's working on the next generation of the intelligence that they've got to pour into it and continue that cadence. And of course, we scale the company accordingly. >> Great news from NGD Systems. Nadir. >> It is wonderful, this FMS coming up, we are announcing there are new generation of product, as well as announcing the close partner with one of the hyperscalers that we are introducing the next generation of product. >> Fantastic, Scott Shadley, VP of Marketing. Nadir Salessi, CEO founder. NGD Systems, thanks very much again for being on theCUBE. And to you, once again, thanks for watching this CUBEConversation. Until we meet again, thanks for watching. (energetic music)
SUMMARY :
and Scott Shadley, VP of Marketing. So, the last time we were here we had a great conversation the demand of the storage continues to grow exponentially. So, when I think of NGD Systems, So, that's one of the areas that we of 10 for the same capacity. And that's the challenge that the industry is facing. So, the more they can do inside of the drive Is that the basic notion that we're talking here, and I'll let Scott go into some of the use cases in the way of things like AI and machine learning. and execute the commands in place on the data. So, to put this, kind of summarize this, of the storage from a sketch, we are able of that parallelism closer to the data. And the fact that we can do the densities in the San Bernardino Mountains. So, as we think about where the technology is, So, the new generation of contents, they are large, So, what's the complexity of introducing your product? of the market that nowadays are focused more or other partners that can play off of the system, to push the state of the art from performance smarts of product in mass production, the R&D's working the next generation of product. And to you, once again, thanks
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