What exascale computing could mean for chemistry

https://cen.acs.org/physical-chemistry/computational-chemistry/exascale-computing-mean-chemistry/100/i31

by Trouble_007 • 4 years ago

46 25 4 years ago

cen.acs.org

jes• 4 years ago

Additional info:

https://www.olcf.ornl.gov/frontier/

bawolff• 4 years ago

That's a generous use of the word "info"

There's so many buzzwords you would think they were shilling crypto.

alpineidyll37• 4 years ago

This is exactly like if you were to ask: what can exascale do for larger scale quantum simulation.

Not much! These devices are vanity projects and prey upon people's intellectual blindness in the face of giant numbers.

atty• 4 years ago

This is… amazing misinformed. I am assuming you’ve never done scientific simulation work if you think that. Physical simulations in many fields get better due to increases in compute, memory, and bandwidth faster than they do from algorithmic improvements (there are only so many algorithmic improvements one can make to a PDE solver). And certain problems simply can’t be simulated until a certain amount of compute (and more importantly memory) are available.

And while some of the time the entire cluster will be given to a single large scale project, most of the time it will be acting as a massive GPU farm for all sorts of research. A win-win for everyone.

alpineidyll37• 4 years ago

I have my Ph.D. in this exact field from UC Berkeley. My thesis was about polynomial scaling algorithms for quantum molecular systems. I was a postdoc at Harvard. I received an NSF career award. I know exactly what I'm talking about lol.

These computer platforms are drastically inefficient on a flop / $ basis. They exist to funnel money into the pockets of the companies who assemble them. They never ever achieve even a tiny fraction of their peak rated flops on any calculation that has any scientific meaning.

alpineidyll37• 4 years ago

If you understood anything about how literally every chemistry problem scales non-linearly, and requires exponential amount of sampling to yield any predictive meaning you wouldn't talk about things you don't understand lol. Peta=>Exa equals 1000x so you can get 31x the accuracy in a monte carlo assuming perfect parallelism (at 1000x the cost), and that's one of the better scaling things it could be used for.

It's fun to have big toys sure, it's fun to make big GPU clusters. But if they spent what they spend on this computer, on just funding students to solve problems and toss them a 3090 100000000x more scientific breakthroughs would happen. This machine is 60% paperweight, at best, with a hefty budget for good old fashioned contract pork.

mechagodzilla2• 4 years ago

Alpineidyll already commented on QM calculations, but I can attest these machines are useless for molecular dynamics as well. In order to actually run in any even vaguely “efficient” regime (ie be faster than a single GPU on your exaflop machine), you need to scale the problem to the size that you can no longer approach interesting timescales for the dynamics involved. A 10 nanosecond simulation of a 100M particle system is useless. The problem almost immediately becomes latency bound when you use multiple chips. The first generation Anton machine from DE Shaw Research (which they built in 2008!) is still over an order or magnitude faster than any existing machine (in 2022!) that isn’t a newer Anton when it comes to MD.

If they wanted a GPU farm they could probably have built it for 1/10 the cost or less by throwing out the interconnect and infrastructure that makes it a “supercomputer”.

dekhn3• 4 years ago

I've run sims on supercomputers and other HPC environments. MD and QM simulations really don't solve any problems, they just generate press releases.

Trouble_0072• 4 years ago

Frontier (supercomputer) - Hewlett Packard Enterprise Frontier (OLCF-5) : https://en.m.wikipedia.org/wiki/Frontier_(supercomputer)

TOP-500 » June 2022 : https://www.top500.org/lists/top500/2022/06/

HN discussion of TOP-500 » 67 days ago » 71 comments : https://news.ycombinator.com/item?id=32002830

Aurora exascale Supercomputer – Planned to be completed in late 2022 : https://en.m.wikipedia.org/wiki/Aurora_(supercomputer)

Trouble_0072• 4 years ago

ORNL Celebrates Launch of Frontier – the World’s Fastest Supercomputer : https://www.olcf.ornl.gov/2022/08/17/ornl-celebrates-launch-...

Science at ORNL : https://www.olcf.ornl.gov/leadership-science/

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OLCF researchers win R&D 100 award

Team honored for work on Flash-X software simulation package : https://www.olcf.ornl.gov/2022/09/08/olcf-research-team-wins...

What exascale computing could mean for chemistry

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