78: GreyBeards YE2018 IT industry wrap-up podcast

In this, our yearend industry wrap up episode, we discuss trends and technology impacting the IT industry in 2018 and what we can see ahead for 2019 and first up is NVMeoF

NVMeoF has matured

In the prior years, NVMeoF was coming from startups, but last year it’s major vendors like IBM FlashSystem, Dell EMC PowerMAX and NetApp AFF releasing new NVMeoF storage systems. Pure Storage was arguably earliest with their NVMeoF JBOF.

Dell EMC, IBM and NetApp were not far behind this curve and no doubt see it as an easy way to reduce response time without having to rip and replace enterprise fabric infrastructure.

In addition, NVMeoFstandards have finally started to stabilize. With the gang of startups, standards weren’t as much of an issue as they were more than willing to lead, ahead of standards. But major storage vendors prefer to follow behind standards committees.

As another example, VMware showed off an NVMeoF JBOF for vSAN. A JBoF like this improves vSAN storage efficiency for small clusters. Howard described how this works but with vSAN having direct access to shared storage, it can reduce data and server protection requirements for storage. Especially, when dealing with small clusters of servers becoming more popular these days to host application clusters.

The other thing about NVMeoF storage is that NVMe SSDs have also become very popular. We are seeing them come out in everyone’s servers and storage systems. Servers (and storage systems) hosting 24 NVMe SSDs is just not that unusual anymore. For the price of a PCIe switch, one can have blazingly fast, direct access to a TBs of NVMe SSD storage.

HCI reaches critical mass

HCI has also moved out of the shadows. We recently heard news thet HCI is outselling CI. Howard and I attribute this to the advances made in VMware’s vSAN 6.2 and the appliance-ification of HCI. That and we suppose NVMe SSDs (see above).

HCI makes an awful lot of sense for application clusters that VMware is touting these days. CI was easy but an HCI appliance cluster is much, simpler to deploy and manage

For VMware HCI, vSAN Ready Nodes are available from just about any server vendor in existence. With ready nodes, VARs and distributors can offer an HCI appliance in the channel, just like the majors. Yes, it’s not the same as a vendor supplied appliance, doesn’t have the same level of software or service integration, but it’s enough.

[If you want to learn more, Howard’s is doing a series of deep dive webinars/classes on HCI as part of his friend’s Ivan’s ipSpace.net. The 1st 2hr session was recorded 11 December, part 2 goes live 22 January, and the final installment on 5 February. The 1st session is available on demand to subscribers. Sign up here]

Computional storage finally makes sense

Howard and I 1st saw computational storage at FMS18 and we did a podcast with Scott Shadley of NGD systems. Computational storage is an SSD with spare ARM cores and DRAM that can be used to run any storage intensive, Linux application or Docker container.

Because it’s running in the SSD, it has (even faster than NVMe) lightening fast access to all the data on the SSD. Indeed, And the with 10s to 1000s of computational storage SSDs in a rack, each with multiple ARM cores, means you can have many 1000s of cores available to perform your data intensive processing. Almost like GPUs only for IO access to storage (SPUs?).

We tried this at one vendor in the 90s, executing some database and backup services outboard but it never took off. Then in the last couple of years (Dell) EMC had some VM services that you could run on their midrange systems. But that didn’t seem to take off either.

The computational storage we’ve seen all run Linux. And with todays data intensive applications coming from everywhere these days, and all the spare processing power in SSDs, it might finally make sense.

Futures

Finally, we turned to what we see coming in 2019. Howard was at an Intel Analyst event where they discussed Optane DIMMs. Our last podcast of 2018 was with Brian Bulkowski of Aerospike who discussed what Optane DIMMs will mean for high performance database systems and just about any memory intensive server application. For example, affordable, 6TB memory servers will be coming out shortly. What you can do with 6TB of memory is another question….

Howard Marks, Founder and Chief Scientist, DeepStorage

Howard Marks is the Founder and Chief Scientist of DeepStorage, a prominent blogger at Deep Storage Blog and can be found on twitter @DeepStorageNet.

Raymond Lucchesi, Founder and President, Silverton Consulting

Ray Lucchesi is the President and Founder of Silverton Consulting, a prominent blogger at RayOnStorage.com, and can be found on twitter @RayLucchesi. Signup for SCI’s free, monthly e-newsletter here.

72: GreyBeards talk Computational Storage with Scott Shadley, VP Marketing NGD Systems

For this episode the GreyBeards talked with another old friend, Scott Shadley, VP Marketing, NGD Systems. As we discussed on our FMS18 wrap up show with Jim Handy, computational storage had sort of a coming out party at the show.

NGD systems started in 2013 and have  been working towards a solution that goes general availability at the end of this year. Their computational storage SSD supplies general purpose processing power sitting inside an SSD. NGD shipped their first prototypes in 2016, shipped FPGA version of their smart SSD in 2017 and already have their field upgradable, ASIC prototypes in customer hands.

NGD’s smart SSDs have a 4-core ARM processor and  run an Ubuntu Distro on 3 of them.  Essentially, anything that could be run on Ubuntu Linux, including Docker containers and Kubernetes could be run on their smart SSDs.

NGD sells standard (storage only) SSDs as well as their smart SSDs. The smart hardware is shipped with all of their SSDs, but is only enabled after customer’s purchase a software license key. They currently offer their smart SSD solutions in  America and Europe, with APAC coming later.

They offer smart SSDs in both a 2.5” and M.2 form factor. NGD Systemss are following the flash technology road map and currently offer a 16TB SSD in 2.5” FF.

How applications work on smart SSDs

They offer an open-source, SDK which creates a TCP/IP tunnel across the  NVMe bus that attaches their smart SSD. This allows the host and the SSD server to communicate and send (RPC) work back and forth between them.

A normal smart SSD work flow could be

  1. Host server writes data onto the smart SSD;
  2. Host signals the smart SSD to perform work on the data on the smartSSD;
  3. Smart SSD processes the data that has been sent to the SSD; and
  4. When smart SSD work is done, it sends a response back to the host.

I assume somewhere before #2 above, you load application software onto the device.

All the work to be done on smart SSDs could be the same for the attached SSD and the work could easily be distributed across all attached smart SSDs attached and the host processor. For example, for image processing, a host processor would write images to be processed across all the SSDs and have each perform image recognition and append tags (or other results info) metadata onto the image and then respond back to the host. Or for media transcoding, video streams could be written to a smart SSD and have it perform transcoding completely outboard.

The smart SSD processors access the data just like the host processor or could use services available in their SDK which would access the data much faster. Just about any data processing you could do on the host processor could be done outboard, on smart SSD processor elements. Scott mentioned that memory intensive applications are probably not a good fit for computational storage.

He also said that their processing (ARM) elements were specifically designed for low power operations. So although AI training and inference processing might be much faster on GPUs, their power consumption was much higher. As a result, AI training and inference processing power-performance would be better on smart SSDs.

Markets for smart SSDs?

One target market for NGD’s computational storage SSDs is hyper scalars. At FMS18, Microsoft Research published a report on running FAISS software on NGD Smart SSDs that led to a significant speedup. Scott also brought up one company they’re working with that was testing  to find out just how many 4K video  streams can be processed on a gaggle of smart SSDs. There was also talk of three letter (gov’t) organizations interested in smart SSDs to encrypt data and perform other outboard processing of (intelligence) data.

Highly distributed applications and data reminds me of a lot of HPC customers I  know. But bandwidth is also a major concern for HPC.  NVMe is fast, but there’s a limit to how many SSDs can be attached to a server.

However, with NVMeoF, NGD Systems could support a lot more “attached”  smart SSDs. Imagine a scoop of smart SSDs, all attached to a slurp of servers,  performing data intensive applications on their processing elements in a widely distributed fashion. Sounds like HPC to me.

The podcast runs ~39 minutes. Scott’s great to talk with and is very knowledgeable about the Flash/SSD industry and NGD Systems. His talk on their computational storage was mind expanding. Listen to the podcast to learn more.

Scott Shadley, VP Marketing, NGD Systems

Scott Shadley, Storage Technologist and VP of Marketing at NGD Systems, has more than 20 years of experience with Storage and Semiconductor technology. Working at STEC he was part of the team that enabled and created the world’s first Enterprise SSDs.

He spent 17 years at Micron, most recently leading the SATA SSD product line with record-breaking revenue and growth for the company. He is active on social media, a lover of all things High Tech, enjoys educating and sharing and a self-proclaimed geek around mobile technologies.