[HN Gopher] Great timing, supercomputer upgrade lead to successf...
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       Great timing, supercomputer upgrade lead to successful forecast of
       eruption
        
       Author : rbanffy
       Score  : 60 points
       Date   : 2022-06-06 17:37 UTC (5 hours ago)
        
 (HTM) web link (news.illinois.edu)
 (TXT) w3m dump (news.illinois.edu)
        
       | digitallyfree wrote:
       | I wonder if the real-time nature of the model makes it difficult
       | to scale out to run on individual nodes (e.g. something like
       | Folding@Home which sends off compute tasks to volunteer nodes
       | across the world). I would imagine the government, universities,
       | and so forth have lots of idling desktops and servers that could
       | be clustered together into such a system.
       | 
       | Obviously the bureaucracy and management of such a system would
       | be difficult, but it would be an inexpensive way to give these
       | projects additional compute capacity.
        
         | WoahNoun wrote:
         | Unfortunately the finite element software used in the forecast
         | requires a commercial license to run.
         | 
         | https://www.comsol.com/products/licensing
        
         | latchkey wrote:
         | Ethereum will someday (let's not argue on the timing) move to
         | PoS. This will render tens of millions of GPUs idle.
         | 
         | I've been on a quest to find some sort of workload or task
         | runner to take advantage of it and have been coming up empty
         | handed.
         | 
         | The issue is profitability. The capex has been spent... now we
         | just need to find people willing to either risk opex or find
         | profitable workloads.
        
           | paxys wrote:
           | These cards will simply move over to mining the next altcoin
           | on the list, as they all did when Bitcoin was no longer
           | profitable.
        
       | savant_penguin wrote:
       | "This takes an incredible amount of computing power previously
       | unavailable to the volcanic forecasting community"
       | 
       | Could this workload be approximated with neural net models and
       | ran on tpus?
        
         | krastanov wrote:
         | Take a step back. TPUs accelerate any linear algebra so they
         | can accelerate many interesting simulations, not just neural
         | nets. That is much more exciting even if it is tangential to
         | your question. And to be honest, frequently neural net
         | surrogates are just worse than a straightforward "real physics"
         | simulation. There are some cool "Neural ODE" and "physics
         | informed neural nets" research that bridges the gap though.
        
           | nwiswell wrote:
           | > TPUs accelerate any linear algebra
           | 
           | Do they actually? Or do they just accelerate matrix
           | multiplications of a very specific size?
           | 
           | I am not really a domain expert for scientific computing, but
           | for example in finite element analysis, the tetrahedral
           | stiffness matrix is 12x12. Presumably the matrices in fluid
           | flow simulations, climate modeling, etc are also modestly
           | sized, and the challenge has more to do with just _how many
           | total multiplications_ there are.
           | 
           | It is not at all clear to me that an accelerated 128x128
           | multiplication is helpful in these contexts.
        
             | gpm wrote:
             | Presumably finite element analysis involves multiplying
             | many such matricies? Hopefully in parallel?
             | 
             | If so, you can represent them as a Nx12x12 "tensor" for
             | some large N (presumably proportional to the number of
             | elements?), and I'm reasonably sure that's within the realm
             | of what TPUs accelerate well.
        
               | whimsicalism wrote:
               | These are usually iterative methods
        
         | cjbgkagh wrote:
         | They mention porting to machine learning which I assume means
         | neural nets.
        
       | UberFly wrote:
       | Very cool. Hopefully learning to constantly crunch and simulate
       | the fire hose of sensor data at places like this will lead to
       | ever-better earthquake predictions too.
        
       | beastman82 wrote:
       | Hail Alma Mater! nice work.
        
         | jimkleiber wrote:
         | Haha I feel the same way, feels good to see Illinois (do people
         | still call it UIUC?) in the scientific headlines.
        
           | skavi wrote:
           | Just graduated and, yes, we definitely still call it UIUC.
        
             | jimkleiber wrote:
             | Glad to hear! Congrats on graduation. '07 alumnus here.
        
       | myself248 wrote:
       | Out of curiosity, why is an article being written in 2022 about
       | something that happened in 2017-18?
        
         | WoahNoun wrote:
         | The actual scientific paper was just published:
         | 
         | https://www.science.org/doi/10.1126/sciadv.abm4261
        
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       (page generated 2022-06-06 23:00 UTC)