In-Memory, Caching, Persistence

Asian Student Cluster Competition

The ever-popular “calendar segment” is back (yes, that is us being sarcastic) as Dan describes his upcoming trip to Dalian, China for the Asian Student Cluster competition. 20 teams are expected to compete, mostly from mainland China, but also from Europe, South America and other parts of Asia. All of them have gone through a rigorous qualifying process. Chinese vendor Inspur provides all the equipment (except for accelerators, which remain the responsibility of the teams) based on the configuration that the teams request.

As always, the team, and the rest of humanity, is highly supportive of the student cluster tournaments that take place at SC, ISC, and this Asian one, in addition to many regional supporting events.

Dan also lets us know how to go about picking the right seat in the airplane. There’s an app for that!

New Optane

Intel’s new Optane is M.2 format with 16GB or 32GB of Opatne and 256GB, 512GB, or 1TB of Flash backing it. This made Henry think of history of caching and how people used to go through laborious data placement on outer cylinders of hard disks. Then you had DIMMs with Flash behind it. The discussion goes to the algorithms and policies that manage data movement, which is another form of optimizing workload management, and the different combinations of fast/small/expensive capacity backed up with slower/larger/cheaper capacity. And how persistence impacts this equation and to what extent applications may want to optimize around these. Then there is in-memory processing, ram-disk, and how in the future, the ever-increasing size of memory can make those standard practice.

Catch of the Week


Henry is catchless but we can expect a healthy debate. Shahin produces two to make up for it.


Shahin has new reinforcement that IoT and HPC will converge in interesting ways. 1) We all know that IoT is the fountain of data and will generates so much data that you need HPC (and AI) to make sense of them, but 2) what is also very interesting Digital twins will need to simulate and predict the behavior of the real thing.

What we mean when we talk about digital twins

“Watching it prompted me to wonder how much data it takes to create a digital twin. If I had a digital simulacrum of a machine and could apply different environmental or mechanical factors to it, how large could that original simulacrum be? It turns out that’s not how digital twins work. They aren’t virtual doppelgangers. They are actually a series of algorithms that connote how machine moves or behaves. In other words, a twin isn’t a twin so much as it’s…math.”


Amazon Workers Are Listening to What You Tell Alexa


Shahin thinks it’s as simple as supervised learning needing supervisors, so the question is the legal framework and jurisdiction issues, and social policy, and not technology.


It is time to panic more as Dan shares the story of the Chinese scientist who’s presumably blended monkey and human genes. It’s Planet of the Apes all over again.

Chines Scientists Gene-Hacked Super Smart Human-Monkey Hybrids

“For the first time, scientists have used gene-editing techniques to make monkey brains more humanlike. The monkeys, rhesus macaques, got smarter — they had superior memories to unaltered monkeys, according to recently-published research that’s kicked off a fiery debate among ethicists about how far scientists should be able to take genetic experimentation.”

Listen in to hear the full conversation.

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