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A Look Inside Oak Ridge Lab's Supercomputing Facility
1sockchuck writes "Three of the world's most powerful supercomputers live in adjacent aisles within a single data center at Oak Ridge National Laboratory in Tennessee. Inside this facility, technicians are busy installing new GPUs into the Jaguar supercomputer, the final step in its transformation into a more powerful system that will be known as Titan. The Oak Ridge team expects the GPU-accelerated machine to reach 20 petaflops, which should make it the fastest supercomputer in the Top 500. Data Center Knowledge has a story and photos looking at this unique facility, which also houses the Kraken machine from the University of Tennessee and NOAA's Gaea supercomputer."
Have gnu, will travel.
Well, maybe THIS YEAR will finally be the year of the linux supercomputer.
D'OH!
Only the fastest in the top 500? Not the fastest there is?
Where is the T-437 Safety Command Console? and the big board of nuke plants
the final step in its transformation into a more powerful system that will be known as Titan.
Oh, that is not even its final form.
" which should make it the fastest supercomputer in the Top 500"
At first I thought this was redundant, but then I wondered if there are faster supercomputers that simply are not independently verified to be in the top 500 supercomputers. Anyone have any more info, or am I just overthinking this?
See my journal for slashdot ID's by year. Mine created in 2005. http://slashdot.org/journal/289875/slashdot-ids-by-year
I went there my Sophomore year to check out Oak Ridge. I didn't go for computing ,but since my guide knew that I like computing, he took me to look at the supercomputers. It's this huge room that was visible through glass windows which looked essentially like a huge clean, white, office floor with all the cubicles removed and with the supercomputers in place instead.
At that time (2009?) I heard it wasn't really the fastest supercomputer but it's awesome to hear they're revving it up to that. If I didn't hate TN so much, I'd go to UTK and try to work there for Theoretical Physics with the prospect of one day contributing to some simulation that could run on it--granted people deem me smart enough to join that sort of thing. Sigh...dreams...
Ah, one of my favorite films. Still stands up even today.
I really, really wish articles would stop saying that computer X has Y GFLOPS. It's almost meaningless, because when you're dealing with that much CPU power, the real challenge is to make the communications topology match the computational topology. That is, you need the physical structure of the computer to be very similar to the structure of the problem you are working on. If you're doing parallel processing (and of course you are, for systems like this), then you need to be able to break your problem into chunks, and map each chunk to a processor. Some problems are more easily divided into chunks than other problems. (Go read up on the "parallel dwarves" for a description of how things can be divided up, if you're curious.)
I'll drill into an example. If you're doing a problem that can be spatially decomposed (fluid dynamics, molecular dynamics, etc.), then you can map regions of space to different processors. Then you run your simulation by having all the processors run for X time period (on your simulated timescale). At the end of the time period, each processor sends its results to its neighbors, and possibly to "far" neighbors if the forces exceed some threshold. In the worst case, every processor has to send a message to every other processor. Then, you run the simulation for the next time chunk. Depending on your data set, you may spend *FAR* more time sending the intermediate results between all the different processors than you do actually running the simulation. That's what I mean by matching the physical topology to the computational topology. In a system where the communications cost dominates the computation cost, then adding more processors usually doesn't help you *at all*, or can even slow down the entire system even more. So it's really meaningless to say "my cluster can do 500 GFLOPS", unless you are talking about the time that is actually spent doing productive simulation, not just time wasted waiting for communication.
Here's a (somewhat dumb) analogy. Let's say a Formula 1 race car can do a nominal 250 MPH. (The real number doesn't matter.) If you had 1000 F1 cars lined up, side by side, then how fast can you go? You're not going 250,000 MPH, that's for sure.
I'm not saying that this is not a real advance in supercomputing. What I am saying, is that you cannot measure the performance of any supercomputer with a single GFLOPS number. It's not an apples-to-apples comparison, unless you really are working on the exact same problem (like molecular dynamics). And in that case, you need some unit of measurement that is specific to that kind of problem. Maybe for molecular dynamics you could quantify the number of atoms being simulated, the average bond count, the length of time in every "tick" (the simulation time unit). THEN you could talk about how many of that unit your system can do, per second, rather than a meaningless number like GFLOPS.
"UNITE with the Campaign for a Free Internet because today, our future begins with tomorrow!"
Freedom for more posts from people like you? I might need to reconsider this whole net neutrality thing...
So this is where they make all the Pokemons
I would think density would matter more than the total weight as far as relativistic effects on that scale. I would think sanity also matters when it comes to evaluating such effects too.
See subject-line above - I/O latencies matter for certain types of processing also is why I asked (SSD vs. HDD, & caching methods in hardware (ala caching controllers OR onboard FLASH "Hybrid" caching etc./et al)).
* Just curious, & Thanks-In-Advance for the information on the I/O architecture in the area of disks...
APK
P.S.=> It'd be interesting to know, outside of clustering + CPU/GPU processing specs, which seems to mostly (and perhaps rightfully so) what folks concern themselves here with in these "supercomputers"...
... apk
The US still has these Big Science centers left over from the glory years. There's Oak Ridge, Los Alamos, and the Lawrence Livermore Senior Activity Center (er, "stockpile stewardship"), plus the NASA centers. Their original missions (designing bombs, sending people to the Moon) are long gone, but nobody turned off the money, so they keep looking for something, anything, to justify the pork.
The atomic centers are all located in the middle of nowhere. This was originally done for good reasons - their existence was originally secret, and something might blow up. (Well, Lawrence Livermore was in the middle of nowhere, but the Bay Area has grown to reach it.) As a result, they're major employers in their states, so they have unusual political clout.
The question is whether this is a good way to do science. Should that funding go through NSF instead?
it would be funnier if it were named 'tighten'.
The Story of Supercomputing at Oak Ridge would not be complete without the Stone Soupercomputer, built from surplus secretaries computers in the late 1990's
http://en.wikipedia.org/wiki/Stone_Soupercomputer
Isn't putting a super computer called Titan in a superconducting-magnet research complex founded during the Manhattan Project; just asking for some sort of resonance cascade failure?
Looks like they clustered some Pepsi machines
While it's certainly fascinating to hear about the machine itself, it's easy to forget part of why it exists: simulating destruction. The Manhattan Project also came from Oak Ridge, if you recall.
As someone who lives in the region, nobody is particularly keen on what possibly goes on at these places. There are various "secret" military installations scattered around here, from Oak Ridge to Holston Army Ammunition. Between what we factually know is buried under and developed at these places, and what is rumored to, it can be a bit unnerving at times to consider that you live in what amounts to one of the ground zeroes of the country if anyone ever decided to start trouble. Or, likewise, ground zero if anything were to go catastrophically wrong.