Topics including (but not limited to)....

  • Rising power needs

  •  

    Advanced cooling

  •  

     

     

     

       Latest & Greatest New Tech

  • How compute is used

  • Efficient computing & explaining stuff

  •   We argue about it all!

Radio Free HPC (RFHPC) started in 2012 and, after a short break of 193 months, has returned to the airwaves (cyber waves?) with co-hosts Dan Olds, Henry Newman, and Shahin Khan.

The podcast covers a wide range of topics but is particularly focused on data center technology and challenges. These include high performance computing, power and cooling, new technology, and, really, whatever the hell they want to talk about.

 

Quick FAQ


"Why are you just covering HPC? There's this new thing called AI, have you heard of it?"

Yeah, we've heard of it and we do cover it. To us, HPC is a broad term used to refer to a very broad group of apps/workloads that have common characteristics.

  1. They are computationally intense
  2. Time to solution and quality of solution are critical
  3. The output is important enough to justify investment in high-end clusters and associated hardware/software

AI meets all of the criteria above just like bioscience, aerospace, weather prediction, and several other domains. In fact, AI is or will soon be folded into the workflows of nearly every 'traditional' HPC and enterprise application over time. This is going to put a lot of pressure on data centers and we'll be talking about how to deal with it.

 

"Was the old version of Radio Free HPC popular? I've never heard of it..."

Yes, it rose from obscurity to being mildly popular and, at times, entertaining. At our peak, we had as many as 16 sustained listeners and as many as 19 theoretical max listeners.

 

"I listened to the old show a couple of times and liked the arguing. Will there be more of that in this reboot?"

Yes, in fact we expect as much as 29% more arguing and a significant increase in the number of personal insults per episode.

 

"How often will this thing come out and how do I find out about it?"

We used to try to do weekly shows but failed due to other commitments, travel, etc. And there were just weeks when nothing important happened. But to answer your question, could be every couple of weeks, could be once a month, or we could record a marathon 8-10 hour single episode. Depends on what's happening and our mood.

We're getting together our RSS feeds and such but in the short term we'll be publicizing the episodes through the RFHPC X account and our individual social media accounts.

 

Ok, enough questions. If you want to learn more about the show and hosts, check out the "About" page.

Here are our most recent episodes along with the 345 or so previous editions, enjoy!

 

 

 

Latest Episode

  • Episode 248: Turing Machine is Sequential, How About a Parallel Machine?

    By admin | October 13, 2019 |

    Solving Exponential Problems in Polynomial Time

    Pretty much all of computing rests on the strong foundation of the Turing Machine, a general purpose formulation of computing which happens to be very sequential. It transfers that attribute to the Von Neumann architecture that manifests it and leads to the famous Von Neumann bottleneck.

    It would be good if an inherently parallel foundation existed. That requires a blending of computing and memory and has led to approaches to build processor-in-memory or computational memory systems. If successful, it could help reach the nirvana of solving (some?) exponential problems in polynomial time by exposing the intrinsic parallelism of large scale problems.

    The @RadioFreeHPC team delves into this topic with the folks at MemComputing, a San Diego startup that’s built a new parallel foundation for computing. It calls it the universal memcomputing machine, and a “realization of self-organizing circuits”.

    It’s a lively discussion with co-founders John Beane, CEO, and Fabio Traversa, CTO of the company. Just in emulation mode on existing hardware, and on the right (exponentially growing) applications, the technology has performed so well as to lead the company to offer it as a service now instead of waiting to build custom hardware, and to make them think of Quantum Computing kinds of performance.

    Here are a few slides followed by the relevant academic paper. Click on the images to expand them, and click on the paper’s title to see the PDF on Arxiv.org.

    Universal Memcomputing

    We introduce the notion of universal memcomputing machines (UMMs): a class of brain-inspired general-purpose computing machines based on systems with memory, whereby processing and storing of information occur on the same physical location. We analytically prove that the memory properties of UMMs endow them with universal computing power—they are Turing-complete—, intrinsic parallelism, functional polymorphism, and information overhead, namely their collective states can support exponential data compression directly in memory.

    Henry Newman’s Why No One Should be Online, Ever.

    Election security is going to be a big issue in the coming months and years. Elections have been classified as “Critical Infrastructure”, which has serious implications for Federal and state officials.

    Henry reports that the US Attorney for West Virginia has issued a statement about election security and concerns about the vulnerability of the state’s election system.

    United States Attorney Mike Stuart Issues Statement on Election Security

    CHARLESTON, W.VA. – United States Attorney Mike Stuart issued the following statement about the important issues of elections, election security and voter legitimacy:
    “During the 2018 election cycle, Secretary of State Warner referred to my office what he perceived to be an attempted intrusion by an outside party into the West Virginia military mobile voting system. I note that there was no intrusion and the integrity of votes and the election system was not compromised.  My office instituted an investigation to determine the facts and whether any federal laws were violated. The FBI has led that investigation.  That investigation is currently ongoing and no legal conclusions whatsoever have been made regarding the conduct of the activity or whether any federal laws were violated.

    Catch of the Week

    Shahin talks about the work that DOE labs are doing to better understand the impact of AI on science.

    DOE Sets Sights on Accelerating AI (and other) Technology Transfer

    For the past two days DOE leaders along with ~350 members from academia and industry gathered in Chicago to discuss AI development and the ways in which industry and DOE could collaborate to foster AI commercialization. The occasion was DOE’s fourth InnovationXLab Summit – the earlier three summits were on advanced manufacturing; grid modernization; and energy storage. Two more are planned: bio-manufacturing in January and quantum science in the late spring.

    Henry points out eight new storage-related patents granted to Intel, 2 of which look quite important for emerging storage systems. Here are the two patents here and here, and a link to the article:

    Intel Assigned Eight Patents

    Erase block granularity eviction in host based caching, persistently caching storage data in page cache, drive-based storage scrubbing, processors, methods, systems, and instructions to load multiple data elements to destination storage locations other than packed data registers, secure memory, techniques for command validation for access to storage device, authenticating system to enable access to diagnostic interface in storage device, techniques for moving data between network i/ot device and storage device

    Dan is concerned that bots are overstepping their boundaries and talks about research at Microsoft that can generate fake comments for online articles.

    This won’t end well. Microsoft’s AI boffins unleash a bot that can generate fake comments for news articles

    Please no, we don’t need a machine-learning troll farm

    As if the internet isn’t already a complicated cesspool full of trolls, AI engineers have gone one step further to build a machine learning model that can generate fake comments for news articles.

    Listen in to hear the full conversation.

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