114: GreyBeards talk computational storage with Tong Zhang, Co-Founder & Chief Scientist, ScaleFlux

Seeing as how one topic on last years FMS2020 wrap-up with Jim Handy was the rise of computational storage and it’s been a long time (see GreyBeards talk with Scott Shadley at NGD Systems) since we discussed this, we thought it time to check in on the technology. So we reached out to Dr. Tong Zhang, Chief Scientist and Co-founder, ScaleFlux to see what’s going on. ScaleFlux is seeing rising adoption of their product in hyper-scalers as well as large enterprises. Their computational storage is a programmable FPGA based 4TB and 8TB SSD.

Tong was very knowledgeable on current industry trends (Moore’s law slowing & others) that have created an opening for computational storage and other outboard compute. He also is well versed into how some of the worlds biggest customers are using the technology to work faster and cheaper in their data centers. Listen to the podcast to learn more.

At the start Tong mentioned Alibaba’s use of ScaleFlux’s transparent, line speed, outboard encryption/decryption and compression/decompression. And, depending on the data, they can see compression ratios far exceeding 2:1. As such, customers not only benefit from a cheaper $/GB but can also see better NAND endurance and higher performance.

Hosts can do compression and encryption but doing so takes a lot of CPU cycles. It turns out that compression is more compute intensive than encryption. Tong said that most modern cores can encrypt/decrypt at 1GB/sec but, depending on the compression algorithm, can only compress at 40 to 100MB/sec. But in any case doing so on the host consumes a lot of CPU instruction cycles. With ScaleFlux, they can compress and decompress at PCIe bus speeds.

Most storage controllers that offer compression/decompression must have some sort of LBA (logical block address) virtualization. Because while the host may be writing 512 or 4096 byte blocks, what’s actually written to the NAND is more like, 231 or 1999 bytes. So packing these odd, variable length blocks into NAND blocks can become a problem. But most SSDs already have a flash translation layer (FTL) where LBA addresses are mapped, over time, to different physical NAND page/block addresses. ScaleFlux has combined support for LBA virtualization and FTL into the same process and by doing so, they reduce IO overhead to perform better.

ScaleFlux’s drive is an NVMe SSD, which already supports great native response times but when you are transferring 1/2 or less of (compressed) data from the host onto NAND, you can reduce latencies even more. .

Although their current generation product is based on TLC NAND they are working on the next generation which will support QLC. And the benefits of writing and reading less data should also help QLC endurance and performance.

Although ScaleFlux is seeing great adoption with just outboard transparent compression and encryption, there is more that could be done, For example,

  • Filtering query’s at the drive rather than at the host. If customers can send a search key/phrase or other filtering request directly to the drive, the drive can pass over all it’s data and send back just the data that matches that filter request.
  • Transcoding and other data format changes. Although transcoding makes a lot of sense to do outboard, Tong also mentioned format changes. We asked him to clarify and he said consider a row based database that needs to be accessed in columnar format. If the drive could change the format from one to the other, it opens up more analytics tool sets.

At the moment, ScaleFlux engineering teams are the ones that program the FPGA to perform outboard functionality. But in a future release, they plan to adding ARM cores in a SoC, which can handle more general purpose outboard functionality as code.

Because of this added complexity of compression, encryption and other outboard logic, we asked Tong what power loss protection was available at the drive level. Tong assured us that once data has been received by their device, it is maintained across a power failure with CAPs and other logic to offload it.

Tong also mentioned that Intel, AWS and the NVMe standard committee are looking at adding some computational storage support into the NVMe standard, so applications and host software can invoke and maybe modify outboard functionality on the fly. Sort of like loading containers of functionality to run on the fly on an SSD drive.

Dr. Tong Zhang, Chief Scientist and Co-fonder, ScaleFlux

Dr. Tong Zhang is a well-established researcher with significant contributions to data storage systems and VLSI signal processing. Dr. Zhang is responsible for developing key techniques and algorithms for ScaleFlux’s Computational Storage products and exploring their use in mainstream application domains.

He is currently a Professor at Rensselaer Polytechnic Institute (RPI). His current and past research span over database, filesystem, solid-state and magnetic data storage devices and systems, digital signal processing and communication, error correction coding, VLSI architectures, and computer architecture.

He has published over 150 technical papers at prestigious USENIX/IEEE/ACM conferences and journals with the citation h-index of 36, and has served as general and technical program chairs for several premier conferences. Among his many research accomplishments, he made pioneering contributions to establishing flash memory signal processing and enabling practical implementation of low-density parity-check (LDPC) codecs. He received two best paper awards and has over 20 issued/pending US patent applications.

He holds BS/MS degrees in EE from the Xi’an Jiaotong University, China, and PhD degree in ECE from the University of Minnesota.

113: GreyBeards talk storage for next gen. workloads with Liran Zvibel, Co-Founder & CEO WekaIO

Sponsored By:

I’ve known Liran Zvibel, Co-founder and CEO of Weka IO for many years now and it’s the second time he’s been on our show, (see: Episode 56: GreyBeards talk high performance file storage...). In those days, WekaIO was just coming out and hitting the world with this extremely high-performing, scale out unstructured data solution. Well since then, they’ve just gotten better.

Keith and I had a great time talking with Liran again. Liran has deep knowledge about unstructured data and how enterprises use it these days. WekaIO’s story, over the last two years has gone beyond great performance to real world, hybrid cloud offerings e as well as going after the cloud native app’s (read Kubernetes [K8S]) persistent storage. Listen to the podcast to learn more.

We started with a history lesson on WekaIO. Back in those days (which persists today, I might add) there were many IO workloads that required companies to purchase different solutions for different work. For example, they needed DAS or SAN for performance, NAS for ease of access and object for scale. WekaIO came out with an answer to all these problems in a single, scaleable storage system. That is, they performed IO as fast as DAS or SAN block, had all the ease of access of NAS, and could scale as much as object.

However, the real culprit holding the world back was “NFS”. At the outset NFS was designed (back in the 1990s) with the then current networking speeds available (10-100Mbps), which performed just fine at those speeds. But when 10-100GbE came out in the 2000’s, NFS’s metadata overhead was too chatty to support wire speeds. Thus, any storage that depended on NFS protocols couldn’t supply (small) files fast enough for modern applications.

This is why WekaIO has moved to not only support NFS and SMB but also POSIX and NVIDIA® GPUDirect® Storage interfaces. By offering POSIX, WekaIO is able to plug into standard Linux and Windows server systems and provide excellent small file performance. Of course applications that demand small file performance today are mostly data analytics and AI/ML/DL workloads.

Consequently., NVIDIA came out with their GPUDirect Storage protocol to address getting small file (data) into GPUs faster. With GPUDirect, storage systems can RDMA data directly from storage to GPU memory and vice versa, with no OS intervention (other than to set up the transfer). If you happen to have a small file, high performing storage system attached to your fabric that supports GPUDirect , like WekaIO, you can significantly speed up your AI/ML/DL workloads.

Next we started talking K8S storage. WekaIO usestheir POSIX interface in their CSI plugin to support K8S container persistent storage. Again, supplying high performance for small files seems to be tailor made for K8S container applications that exist today and will for the foreseeable future.

Enter the cloud. Almong other things, WekaIO is a AWS primary storage vendor. It also offers snap to cloud. And with both of these in tandem, it’s just become a lot easier to move and access your unstructured data in the cloud. Liran mentioned that WekaIO primary storage in AWS operates across AZ’s. This means it can be configured to support better availability than EBS.

Large BioPharma companies are using WekaIO in AWS to store and process field data and research data, so that this work can be done around the world. Some companies have run out of compute in a single AZ (unbelievable I know but it’s COVID). By offering multi-AZ support unstructured data access with WekaIO, these companies can spread their compute across AZ’s and region and still access their data. And when their products are ready for gov’t certification, having all this data in the cloud, can make provide an easy way to have gov’t access this same data.

Liran Zvibel, Co-founder and CEO WekaIO

As Co-Founder and CEO, Mr. Liran Zvibel guides long term vision and strategy at WekaIO. Prior to creating the opportunity at WekaIO, he ran engineering at social startup and Fortune 100 organizations including Fusic, where he managed product definition, design, and development for a portfolio of rich social media applications.

Liran also held principal architectural responsibilities for the hardware platform, clustering infrastructure and overall systems integration for XIV Storage System, acquired by IBM in 2007.

Mr. Zvibel holds a BSc.in Mathematics and Computer Science from Tel Aviv University.

112: GreyBeards annual year end wrap-up with Keith & Matt

It’s the end of the year, so time for our regular year end wrap up discussion with the GreyBeards. 2020 has been an interesting year to say the least. It started out just fine, then COVID19 showed up and threw a wrench in everyone’s plans and as the year closes, we were just starting to see some semblance of the new normal, when one of the largest security breaches in years shows up. Whew, almost glad that’s over and onto 2021.

As always the GreyBeards had a great discussion on these and other topics to highlight the year just past. The talk was wide ranging and hard to characterize but I did my best below. Listen to the podcast to learn more.

COVID19s impact on the enterprise

It will probably take some time before we learn the true, long term impacts of COVID19 on IT but one major change has to be the massive Work From Home (WFH) transition that took place overnight.

While WFH can be more productive for some, the lack of face2face interaction can be challenging for others. The fact that many of the GreyBeards have been working from home for decades now, left us a bit oblivious to how jarring this transition can be for newcomers.

There’s definitely some psychological changes that need to occur to be productive at WFH. Organization skills become even more important. Structured interactions (read conference calls, zoom/webex and other forms of communication become much more important. And then there’s security.

Turns out VMware and others have been touting VDI solutions for the past decade or so to better support remote work and at the same time providing corporate levels of security for remote work. While occasionally this doesn’t work quite as well as expected, it’s certainly much much better than having end users access corporate data without any security around that data or worse yet, the “bring your own device”. All these VDI solutions had a field day when WFH happened.

Many workers found they could be more productive at WFH, due the less distractions, no commute time and more flexible hours. What happens when COVID19 is vanquished to all these current WFHers is anyone’s guess.

We thought there might be less need for large office campuses/buildings. But there’s something to be said for more collaboration and random interactions through face2face meetings that can only occur in an office setting with workers present at the same time. Some organizations will take to this new way of work while others will try to dial WFH back to non-existent. Where your organization fits on this spectrum and why, will be telling across a number of dimensions.

The rise of ARM

There’s been a slow but steady improvement in ARM processors over the last almost half century. Nowadays it’s starting to make a place for itself in the enterprise. ARH has always been the goto microprocessor for low power solutions (like smartphones) but nowadays they are being deployed in the cloud and even the enterprise. These can be used as server processors but even outside servers, ARM cores are showing up in hardware accelerators as the brains behind SmartNICs, DPUs, SPUs, etc.

Keith made mention AWS 2nd generation Graviton 64-bit ARM processor EC2 instances. And yes there’s significant cost ( & power) savings that can be had using AWS Graviton ARM instances. So the cloud is starting to adopt them. Somewhere over the past couple of years I heard that VMware was porting ESX to work on ARM cores.

But apparently, it’s not just as simple as dropping an ARM multi-core processor into a server and recompiling your code and away you go. Applications need a certain amount of optimization to run effectively on ARM processors. And the speed up between non-optimized and optimized versions of an application running on ARM cores is significant.

As for SmartNICs and DPUs, these are data networking hardware accelerators that provide real time processing capabilities needed to keep up with higher speed networking, 100GbE and beyond. These DPUs perform deep packet inspection, data compression, encryption and other services all at wire speeds.. Yes you could devote 1 or more X86 cores to do this, but it’s much cheaper (and more effective) to do this outside the CPU core. Moreover, performing this activity at the network entry point to the server means that much of this data doesn’t have to be transferred back and forth through server memory. So not only does it save CPU core cycles but also memory size and memory & PCIe bus bandwidth. We published a recent podcast with Kevin Deierling, NVIDIA Networking discussing DPUs if you want to learn more.

Pat made mention at (virtual) VMworld their plans to port ESX to the DPU. Keith followed up on this and asked some other exec’s at VMware about this and they said VMware will more likely support DPUs as just another hardware accelerator in their cluster. In either case, CPU cycles should be freed up and this should help VMware use X86 cores more efficiently. And perhaps this will help them engage in more CPU constrained environments such as Telcom.

Then there’s computational storage. We have been watching this technology for a couple of years now and it’s seeing some success in being deployed to public cloud environments. They seem to be being used to provide outboard data compression. It’s unclear whether these systems depend on ARM processing or not but my bet is that they do. To learn more about computational storage check out these podcasts, FMS2020 wrap up with Jim Handy and our talk with Scott Shadley on NGD’s computational storage.

System security

At yearend, we are learning of a massive security breach throughout US government IT facilities. All based on what is believed to be a Russian hack to a software package that is embedded in a popular networking tool software solution, SolarWinds. They are calling this a software supply chain hack. Although we are mainly hearing about government agencies being hacked, SolarWinds is also pervasive in the enterprise as well.

There have been many hardware supply chain hacks in the past, where a board supplier used chips or logic that weren’t properly vetted. Over time, hardware suppliers have started to scrutinize their supply chains better and have reduced this risk.

And the US government have been lobbying for the industry to use a security chip with a backdoor or to supply back doors to smartphone encryption capabilities. Luckily, so far, none of these have been implemented by industry.

What Russia has shown us is that this particular hack is not limited to the hardware sphere. Software supply chain risk can’t be ignored anymore.

This means that any software application supplier will need to secure their supply chain or bring it all in house. Which may mean that costs for these packages will go up. It’s possible that using a pure open source supply chain may reduce this risk as well. At least that’s the promise of open source.

We said 2020 was an interesting year and it’s going out with a bang.

Matt Leib (@MBLeib), one of our co-hosts, has been blogging in the storage space for over 10 years, with work experience both on the engineering and presales/product marketing.. His blog is at Virtually Tied to My Desktop and he’s on LinkedIN.

Keith Townsend (@CTOAdvisor) is a IT thought leader who has written articles for many industry publications, interviewed many industry heavyweights, worked with Silicon Valley startups, and engineered cloud infrastructure for large government organizations. Keith is the co-founder of The CTO Advisor, blogs at Virtualized Geek, and can be found on LinkedIN.

111: GreyBeards talk data analytics with Matthew Tyrer, Sr. Mgr. Solutions Mkt & Competitive Intelligence, Commvault

Sponsored by:

I’ve known Matthew Tyrer, Senior Manager Solutions Marketing and Competitive Intelligence, Commvault for quite awhile now and he’s always been knowledgeable about the problems the enterprise has in supporting and backing up large file data repositories. But lately he’s been focused on Commvault Activate their data analytics solution.

We had a great talk with Matthew. He was easy to talk to and knew a lot about how data analytics can ease the operational burden of the enterprise growing file data environments. .Remind me not to have two Matthew’s on the same program ever again. Listen to the podcast to learn more.

Matthew mentioned that their Activate was built on the Commvault platform software stack, which has had a rich and long history of development and customer deployments. It seems that Activate data analytics had been an early part of the platform but recently was split out as a separate solution.

One capability that Activate has that many other data analytics solutions do not, is the ability to examine both online data as well as data in backups. Most analytics solution can do one or the other, only a few do both. But if a solution only has access to online or backup data, they are missing half the story.

In addition, Activate can operate across multiple data centers as well as across multiple public cloud environments to provide analytics for an enterprise’s file data where it may reside.

Given the proliferation of file data these days, data analytics has become a necessity to most large IT shops. In the past, an admin could track some data over time but with the volumes of file data today, this is no longer tenable. At PB or more of file data, located in on prem data centers as well as across multiple clouds, there’s just too much file data to keep track of manually anymore.

Activate also indexes file content to provide more visibility and tracking of the different types of data under management in the enterprise. This is in addition to the extensive metadata that is collected and analyzed so it can better understand data access rights, copies and physical locations around the enterprise.

Activate can help organizations govern their data flows in support of industry as well as government data compliance requirements. Activate Data Governance, one of the three Activate solutions, is focused exclusively on providing enterprises the tools needed to manage any and all data that exists under compliance regulation environments.

Mat Leib had worked in eDiscovery before and it had always been a pain to extract “legally relevant” data from online and backup repositories. With the Activate eDiscovery solution and Activate’s content indexing of all file data, legal can perform their own relevant data searches to create eDiscovery data sets in support of litigation activities. Self service legal extracts like this vastly reduces the admin time and cost needed for eDiscovery.

The Activate File Space Optimization solution was deployed in one environment that had ~20PB of data online. By using File Space Optimization, the customer was able to cut 20PB down to 10PB. Any customer could benefit from such a reduction but customers doing data migration would see even more benefit.

At the end of the podcast, Matthew mentioned some videos that show Activate solution use cases.

Matthew Tyrer, Senior Solutions Marketing and Competitive Intelligence

Having worked at Commvault for over twelve years, after 8 years as a Sales Engineer Matt took that technical knowledge and transitioned to marketing where he is currently serving as a Senior Manager in Commvault’s Solution Marketing team. He is also heavily involved in Competitive Intelligence initiatives, and actively participates in field enablement programs.

He brings over 20 years’ experience in the IT industry, including within the fields of data and information management, cloud, data governance, enterprise storage, disaster recovery, and ultimately both implementing and supporting those projects and endeavours for public and private sector clients across Canada and around the globe.

Matt’s passion, deep product knowledge, and broad field experiences have enabled him to translate Commvault technology and vision such that their value is easily understood in the market and amongst client and partner families.

A self-described geek-dad, Matt is an avid boardgame enthusiast, firmly believes that Han shot first, and enjoys tormenting his girls with bad dad jokes.

110: GreyBeards talk FMS2020 wrap up with Jim Handy, General Director of Objective Analysis

This months it’s back to storage and our annual wrap-up on the Flash Memory Summit Conference with Jim Handy, General Director of Objective Analysis. Jim’s been on our show 5 times before and is a well known expert on NAND and SSDs (as well as DRAM and memory systems). Jim also blogs at TheSSDGuy.com and TheMemoryGuy.com just in case you want to learn more.

FMS went virtual this year and had many interesting topics including how computational storage is making headway in the cloud, 3D QLC is hitting the enterprise with PLC on the way, and for a first at FMS, a talk on DNA storage (for more information on this, see our podcast with CatalogDNA). Jim’s always interesting to talk with to help us understand where the NAND-SSD industry is headed. Listen to the podcast to learn more.

Jim mentioned that the major NAND vendors are all increasing the number of layers for their 3D NAND, and it continues to scale well. Most vendors are currently shipping ~100 layer NAND, with Micron doing more than that. And vendor roadmaps are looking at the possibility of 200 layers or more. Jim doesn’t think anyone knows how high it can go.

Another advantage of 3D NAND is it can be used to make bigger bit cells and thus have better endurance. From Jim’s perspective more electrons per cell means a better more resilient bit cell.

Many vendors in the nascent persistent memory industry were all hoping that NAND would stop scaling at some point and they would be able to pick up the slack. But NAND manufacturers found 3D and scaling hasn’t stopped at all. This has relegated most persistent memory vendors to a small niche market with the exception of Intel (and Micron).

Jim said that Intel is losing money on Optane every year, ~$5B so far. But Intel knows that chip profitability is tied to economies of scale, volumes matter. With enough volume, Optane will become cheap enough to manufacture that they will make buckets of money from it.

Interestingly, Jim said that DRAM scaling is slowing down. That means there may be an even bigger market for something close to DRAM access speeds, but with increased density and lower cost. Optane seems to fit that description very well.

Jim also mentioned that computational storage is starting to see some traction with public cloud vendors. Computational storage adds generic compute power to inside an SSD which can be used to perform storage intensive functions out at the SSD rather than transferring data into the CPU for processing. This makes sense where a lot of data would need to be transferred back and forth to an SSD and where computational cycles are just as cheap out on the SSD as in the server. For example, for data compression, search, and video transcoding, computational storage can make a lot of sense. (See our podcast with NGD systems for more informaiton).

In contrast, Open-Channel SSDs are making dumb SSDs, or SSDs without any flash translation layer or other smarts needed to make NAND work as persistent storage bin the enterprise. There’s a small group of system providers that want to perform all this functionality at a global scale (or across multiple SSDs) rather than at the local, SSD drive level.

Another topic that hit it’s stride this year at FMS2020 was Zoned Name Spaces (ZNS). ZNS partitions an SSD into separately addressable segments, to allow higher performing sequential (write) access within those zones. As SSD capacity has increased, IO activity has sky-rocketed and this has led to an “IO blender” effect. Within an IO blender, it’s impossible to understand which IO is following a sequential pattern and which is not. ZNS is intended to solve that probplem

With ZNS SSDs, IOs doing sequential access can have their own partition and that way the SSD can understand its sequential IO and act accordingly. It turns out that sequential writes to NAND can perform much, much faster than random writes.

ZNS was invented for SMR (shingled magnetic recording) disks, because these overwrote portions of other tracks (like roof shingles, tracks on SMR disks overlap). We had heard about ZNS at FMS2019 but had thought this just a better way to share access to a single SSD, by carving it up into logical (mini-)volumes. Jim said that was also a benefit but the major advantage is being able to understand sequential IO and write to the SSD more effectively.

We talked some on the economics of NAND flash, disk and tape as storage media. Jim and I see this continuing a trend that’s been going on for years, where NAND storage cost $/GB ~10X more than disk capacity, and disk storage costs $/GB ~10X more than tape capacity. All three technologies continue their relentless pursuit of increasing capacity but it’s almost like train tracks, all three $/GB curves following one another into the future.

On the other hand, high RPM disk seems to have died, and been replaced with SSDs. Disk manufacturers have seen unit declines but the # GB they are shipping continues to increase. Contrary to a number of AFA system providers, disk is not dead and is unlikely to die anytime soon.

Finally, we discussed DNA storage and it’s coming entry into the storage market. It’s all a question of price of the drive and media technology, size of the mechanism (drive?) and read and write access times. At the moment all these are coming down but are not yet competitive with tape. But given DNA technology trends, there doesn’t appear to be any physical barrier that’s going to stop it from becoming yet another storage technology in the enterprise, most likely at a 10X $/GB cost advantage over tape…

Jim Handy, General Director, Objective Analysis

Jim Handy of Objective Analysis has over 35 years in the electronics industry including 20 years as a leading semiconductor and SSD industry analyst. Early in his career he held marketing and design positions at leading semiconductor suppliers including Intel, National Semiconductor, and Infineon.

A frequent presenter at trade shows, Mr. Handy is known for his technical depth, accurate forecasts, widespread industry presence and volume of publication.

He has written hundreds of market reports, articles for trade journals, and white papers, and is frequently interviewed and quoted in the electronics trade press and other media. 

He posts blogs at www.TheMemoryGuy.com, and www.TheSSDguy.com