X-IO Technologies Are Living On The Edge

Disclaimer: I recently attended Storage Field Day 13.  My flights, accommodation and other expenses were paid for by Tech Field Day and Pure Storage. There is no requirement for me to blog about any of the content presented and I am not compensated in any way for my time at the event.  Some materials presented were discussed under NDA and don’t form part of my blog posts, but could influence future discussions.


X-IO Technologies presented on their Axellio Edge product, amongst other things, at Storage Field Day 13 recently. You can see video of the presentation here, and download my rough notes from here.


What Edge?

So what is the “edge”? Well, a lot of data has mass. And I’m not talking about those big old 1.8″ SCSI drives I used to pull from servers when I was a young man. Some applications (think geosciences, for example) generate a bunch of data very close to their source. This data invariably needs to be analysed to realise its value. Which is all well and good, but if you’re sitting on a boat somewhere you might have more data than you can easily transport to your public cloud provider in a timely fashion. Once the dataset becomes big or fast enough, it’s easier to move the application to the data than vice versa. X-IO say Axellio focuses on the situation where “moving the data processing power closer to where the data is being generated – closer to the source” makes sense. This also means you need the appropriate CPU/RAM combination to run the application attached to the large dataset. And that’s what X-IO means by edge computing.


Show Me Your Specs

[image via X-IO Technologies]


2RU form factor

4 socket Intel e5-26xx v4 CPUs

  • 16 to 88 cores and 24 to 176 threads
  • Core optimised or frequency optimised

32 DIMMs, 16GB – 2TB

  • Optional NVDIMMs for storage cache

Industry-Standard NVMe Storage

  • Up to 72x 2.5” NVMe SSDs
  • 460TB of NVMe Flash with 6.4TB NVMe SSDs (1PB coming)
  • >12 Million IOPS, as low as 35 microseconds latency, 60GBs sustained
  • Optane ready

Optional offload modules

  • 2x Intel Phi – CPU extension for parallel compute
  • 2x Nvidia K2 GPU – Video processing, VDI
  • 2x Nvidia P100 Tesla – Sci Comp, Machine Learning
  • Solarflare Precision Timing Protocol (PTP) Packet Capture (PCAP) offload



X-IO’s FabricXpress is the magic that makes the product work as well as it does. X-IO says it extends the native PCIe bus significantly.

PCIe based Interconnect

  • Up to 72 NVMe SSDs – significantly more SSDs
  • Between server modules
  • Offload modules

Dual ported NVMe architecture

  • Allows access to the same data on the same SSD from both servers
  • Shared access for HA solutions
  • Enables independent server behaviour on shared data

[image courtesy of X-IO Technologies]


Networking and Offloading Module


  • 1×16 PCIe per server module for networking
  • Supports standard off the shelf NICs/HCAs/HBAs
  • Supports HHHL or FHHL cards
  • Ethernet, InfiniBand, FC
  • Up to 2x100GbE per module

Offloading Module

  • Two centre modules is replaced with single carrier
  • Holds two FHFL DW, x16 PCIe cards
  • Nvidia P100: +18.6 Teraflops (sp)
  • Nvidia V100: +30 Teraflops (sp)


Doing What at The Edge?

Edge Data Analytics Platform

The point of Axellio Edge is to ingest and analyse data at really very high speeds. The neat thing about this is that a 2RU chassis replaces a rack of scale out gear. X-IO claim that it’s “uniquely qualified for real-time big data analytics”.

[image courtesy of X-IO Technologies]


Conclusion and Further Reading

I hadn’t previously given a lot of thought to the particular use cases X-IO presented as being ideally suited to the Axellio Edge offering. My day job revolves primarily around large enterprises running ridiculously critical and crusty SQL-based applications (eww, legacy). Whilst I’ve had some experience with scientific types doing interesting things with data out in the middle of nowhere, it’s not been at the scale or speed that X-IO talked about. Aside from the fact that there’s a whole lot to like about Axellio in terms of speed and capability in this 2RU box, I also like the range of scenarios that this thing delivers.

We’re working with bigger and bigger data sets, and it’s getting harder and harder to move this close to our compute platform in a timely fashion. Particularly if that compute platform is sitting in public cloud. And even moreso if we have to respect the laws of physics (stupid physics!). Instead of trying to push a whole tonne of data from the source to the application, X-IO have taken a different approach and are bringing the data and processing back to the source.

The Axellio Edge isn’t going to be the right platform for everyone, but it seems that, if the use case lines up, it’s a pretty compelling offering. Coupled with the fact that people I’ve spoken to who have been X-IO customers have been very staunch advocates for the company. The people I had the pleasure of speaking with at X-IO are all very switched on and have put a lot of thought into what they’re doing.

For more information on PCIe, have a look here. You can also find more info on NVM Express here. You can grab a copy of the Axellio data sheet from here, and there’s a good whitepaper on edge computing and IoT that you can find here (registration required).