Podcast – Rob Lalonde on HPC in the Cloud, Machine Learning and Autonomous Cars

Joining us this week is Rob Lalonde, VP & General Manager, Navops at Univa.

About Univa

Univa is the leading independent provider of software-defined computing infrastructure and workload orchestration solutions.

Univa’s intelligent cluster management software increases efficiency while accelerating enterprise migration to hybrid clouds. We help hundreds of companies to manage thousands of applications and run billions of tasks every day.

 Highlights

  • 1 min 6 sec: Introduction of Guest
  • 1 min 43 sec: HPC in the Cloud?
    • Huge migration of workloads to public clouds for additional capacity
    • Specialized resources like GPUs, massive memory machines, …
  • 3 min 29 sec: Cost perspective of cloud vs local HPC hardware
    • Primarily a burst to cloud model today
  • 5 min 10 sec: Good for machine learning or analytics?
  • 5 min 40 sec: What does Univa and Navops do?
    • Cloud cluster automation
  • 7 min 35 sec: Role of Scheduling
    • Job layer & infrastructure layer
    • Diversity of jobs across organizations
  • 9 min 30 sec: Machine learning impact on HPC
    • Survey of Users ~ Results
      • Machine learning not yet in production ~ still research
      • HPC very much linked to machine learning
      • Cloud and Hybrid cloud usage is very high
      • GPUs usage for machine language
    • 15 min 09 sec: GPU discussion
      • Similar to early cloud stories
    • 16 min 00 sec: Concurrency in operations in HPC & machine learning
      • Workload dependency ~ weather modeling
    • 18 min 12 sec: People bring workloads in-house after running in cloud?
      • Sophistication in what workloads work best where
      • HPC is very efficient ~ 1 Million Cores on Amazon : Successful when AWS called about taking all their resources for other customers 🙂
    • 23 min 56 sec: Autonomous cars discussion
      • Processing in the car or offloaded?
      • Oil and Gas exploration example (Edge Infrastructure example)
        • Pre-process data on ship then upload via satellite to find information required
      • 29 min 12 sec: Is Kubernetes in the HPC / Machine Learning world?
        • KubeFlow project
      • 35 min 8 sec: Wrap-Up

Podcast Guest:  Rob Lalonda, VP & General Manager, Navops

Rob Lalonde brings over 25 years of executive management experience to lead Univa’s accelerating growth and entry into new markets. Rob has held executive positions in multiple, successful high tech companies and startups. He possesses a unique and multi-disciplined set of skills having held positions in Sales, Marketing, Business Development, and CEO and board positions. Rob has completed MBA studies at York University’s Schulich School of Business and holds a degree in computer science from Laurentian University.

Podcast – Ash Young talks Everything in your PC is IoT

Joining us this week is Ash Young, Chief Evangelist of Cachengo and OPNFV Ambassador. Cachengo builds smart, predictive storage for machine learning.

NOTE – We had a microphone problem that is solved at the 9 minute 19 second mark of the podcast. Start there if you find the clicking noise an issue

Highlights

  • 1 min 34 sec: Time to Change Basic Storage Architecture
    • Converged Protocol Appliances & Nothing has changed form early 90s
  • 7 min 8 sec: Sounds like Hadoop?
    • Underlying hardware still used proprietary protocols
  • 9 min 19 sec: Single Drive Cluster – it’s built?
    • 24 Servers and 24 Drives in a 1U ; has done 48 drives
    • Working on a new design for 96 drives in a 1U
  • 11 min 52 sec: Truly a Distributed Storage Array
    • Storage focused microservers
  • 13 min 24 sec: Limitations in Operations with Hardware
    • Hinders Innovation
  • 15 min 40 sec: Lessons Learned on Managing Devices
    • Over-dependence on tunneling protocols requiring full networking (e.g. VPN)
    • Move to peer-to-peer network slicing
  • 17 min 28 sec: Software Defined Networking Topology
    • Introduce devices to each other and get out of the way
  • 18 min 33sec: Every Storage Node is Part of the Network
    • Moves into a world of networking challenges
    • Ipv4 cannot support this model
  • 21 min 06 sec: Networking Magic in the Model
    • Peer to Peer w/ Broker Introduction and then Removal from Traffic
    • Scale out for Edge Computing Requires this New Model
    • 5G Energy Cost Savings are a Must
  • 27 min 28 sec: Issues of Powering On/Off Machines to Save Money
    • Creating a massive array of smaller GPUs for Machine Learning
    • Build a fast, cheap, lower power storage system to get started in the model
  • 34 min 09 sec: Doesn’t fit the model that Edge infrastructure will be Cloud patterned
    • Rob makes a point to listeners to consider various ideas in future Edge infrastructure
  • 36 min 48 sec: State of Open Source?
    • Consortium’s and open source standards
    • Creating the lowest common denominator free thing so competitors can build differentiation on top of it for revenue
    • Not a fan of open core models
  • 41 min 44 sec: Does Open Source include Supporting Implementation?
    • Look at the old WINE project financing
    • You can’t just deploy people onsite for free<
  • 48 min 24 sec: Wrap-Up

Podcast Guest: Ash Young,Chief Evangelist of Cachengo

Technology leader with over 20 years experience, primarily in storage. Created the first open source NAS (network attached storage) stack, the first unified block/file storage stack for Linux, the first storage management software, and the list goes on.

Since 2012, I have been heavily involved in NFV (Network Functions Virtualization). I wrote a bunch of the standards and was editor for the Compute/Storage Domain in the Infrastructure Working Group for NFV. And then I started up the open source effort to close the gaps for achieving our vision of the NFVI. This was the precursor to OPNFV.

The best way to understand what I do is to imagine being a high-level marketing exec who comes up with a whiz bang product and business idea, including business plan, competitive analysis, MRD, everything, but now comes the hand-off with your engineering organization, only to hear a litany of nos. Well, I got tired of being told “No, it can’t be done” or “No, we don’t know how to do it”, so I started doing it myself. I call this skill “Rapid Prototyping”, and over the years I have found it to be a very missing gap in the product development process. When Marketing comes up with ideas, we need a way to very efficiently validate the technology and business concepts before we commit to a lengthy engineering cycle.

I’m just one person, working in a company of over 180,000 people and in a very dynamic industry. My ability to get creative and to influence businesses is never a dull moment; and I will probably be 100 years old and still writing open source software.

2/9 Webcast about mixing GPUs & Big Data Analysis

Here’s something from my employer (Dell) that may be interesting to you: it’s about using GPUs for Big Data Analytics.   I meant to discuss/post this earlier, but… oh well.  Here’s the information

Premieres LIVE: 2pm EST (11 AM PST) TODAY  Free  – Register Now!         

What You’ll Learn:

  • Not just for video games any more: GPUs for simulation and parallel processing
  • Impact on business workflows in seismic processing, interpretation and reservoir modeling
  • ROI: 5x performance in 5 days
  • Cost-effective and flexible cluster configurations
  • Show me the metrics: Tangible results from a variety of customers

Need More Details?