Domain: nccs.gov
Stories and comments across the archive that link to nccs.gov.
Comments · 6
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Re:Definition of Exascale Computing
Simulating the airflow over a new car, plane or rocket design.
Weather forecasting
Simulating biochemical networks
etc.See http://www.nccs.gov/wp-content/media/nccs_reports/Science%20Case%20_012808%20v3__final.pdf
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Lustre
Lustre is pretty cool, but it's not magic pixie dust. It won't break the laws of physics and somehow make a single node faster than it would be as a NFS server. It's for situations when a single file server doesn't have the bandwidth to handle lots of simultaneous readers and writers. A "small" Lustre filesystem these days usually has 8-16 object storage servers serving mid-high tens of TB. The high end filesystems have literally hundreds of OSSes and multiple PB served. The largest I know of right now is the 5PB Spider filesystem at Oak Ridge National Labs.
One nice thing about Lustre on the low end is that you can grow it... Start out small and add new OSSes and OSTs as you need them. This often makes sense in Life Sciences and digital animation scenarios where the initial fast storage needs are unknown or the initial budget is limited (but expected to grow). But if you're never planning to get beyond the capacity of a single node or two, Lustre is just going to be overhead. I don't know much about the other clustered filesystem options.
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Total BS
I work with some of the largest supercomputers in the world... and I can tell you that this is BS. There is no way this guy got someone to give him enough cash to put this together without:
1. A Plan of what to buy / build
2. A sound reasoning behind what would be done with the machine.Beyond that... that isn't even that large of a cluster. There are numerous computers on the east coast larger than that... at universities and government research labs (i.e. http://www.nccs.gov/computing-resources/jaguar/ although maybe he doesn't consider Oak Ridge to be on the "East Coast").
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Re:This thing...
Now, the CX1 really is Cray in name only. Don't make the mistake of thinking of Cray as a maker of itty bitty clusters. Oak Ridge has a >30,000 core Cray XT4, NERSC has an almost 20,000-core XT4, and of course Red Storm has over 26,000 cores.
Umm, that is Cray in name only. The real Cray (Seymour) designed from scratch computers which had performance as their only goal, and which shattered the performance standards of their peers. He did not cobble together existing parts in basically the same way a half dozen other companies do. Now, you can argue whether something like the old Cray is even possible anymore, let alone economically viable, but you shouldn't pretend that the current Cray is in the same league.
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Re:This thing...
Are you trying to imply that Cray the company is "in name only?" Because that's not at all the case.
It's true that Cray was a shadow of its former self after Tera bought it, but many of the Tera executives have left, and some of what Cray Research used to be has re-emerged.
Now, the CX1 really is Cray in name only. Don't make the mistake of thinking of Cray as a maker of itty bitty clusters. Oak Ridge has a >30,000 core Cray XT4, NERSC has an almost 20,000-core XT4, and of course Red Storm has over 26,000 cores.
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Re:Are these machines actually used?
In fact, a lattice QCD problem was one of the model problems for the Track 1 proposals. Proposers had to "provide a detailed analysis of the anticipated performance of the proposed system on the following set of model problems...A lattice-gauge QCD calculation in which 50 gauge configurations are generated on an 84^3*144 lattice with a lattice spacing of 0.06 fermi, the strange quark mass m_s set to its physical value, and the light quark mass m_l = 0.05*m_s. The target wall-clock time for this calculation is 30 hours." Full details here.
This is a Big F-ing Problem that does in fact require Big F-ing Computers to solve. To meet the target time would require at least a petaflop of sustained performance; hence the inclusion of this problem in the call for proposals. The other model problems came from CFD and molecular dynamics, and there was a wide range of smaller required problems as well.
Now, none of this explains how these machines will really be used, or to what end. Nevertheless, I can vouch for such large machines being used under heavy load to solve very large problems. Poke around any of the national supercomputing labs' websites, and you should be able to find at least plenty of news releases, if not papers.
Here are some quick samples:
- ASC at Lawrence Livermore National Lab (home of BG/L, Top500 #1)
- NCCS at Oak Ridge National Lab (home of Jaguar, Top500 #2)
- Sandia National Lab (home of Red Storm, Top500 #3)
- NERSC at Lawrence Berkeley National Lab