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$208 Million Petascale Computer Gets Green Light
coondoggie writes "The 200,000 processor core system known as Blue Waters got the green light recently as the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications (NCSA) said it has finalized the contract with IBM to build the world's first sustained petascale computational system.
Blue Waters is expected to deliver sustained performance of more than one petaflop on many real-world scientific and engineering applications. A petaflop equals about 1 quadrillion calculations per second. They will be coupled to more than a petabyte of memory and more than 10 petabytes of disk storage. All of that memory and storage will be globally addressable, meaning that processors will be able to share data from a single pool exceptionally quickly, researchers said. Blue Waters, is supported by a $208 million grant from the National Science Foundation and will come online in 2011."
nah, nevermind
I'm glad they've given it a green light.
Imagine having all that computer power, and not even knowing if it was switched on!
"Be light, stinging, insolent and melancholy"
Can it figure out how to brew the 'perfect' cup of coffee?
Here's to hot beer, cold women, and Glaswegian kisses for all.
Yes, I know this is probably a very naive question, but has anyone here actually had the privilege of working on one of these things? I mean, what do they actually use this for?
I think it's awesome, but are there any concrete advancements that can be attributed to having access to all this computing power?
Just wondering...
If you can read this... 01110101 01110010 00100000 01100001 00100000 01100111 01100101 01100101 01101011
No. This is Urbana,Illinois. HAL 9000 would be more appropriate.
Well.. maybe. Or Maybe not. But Definitely not sort of.
Cool thing about the globally addressable petabyte. That way people writing really crappy code that don't bother thinking about their memory storage can just thrash away. And who cares about pipeline stalls.
I find it funny how the people who have never been formally trained with writing in a language (Mathematics, and just science in general) write the best codes while the majority of the IT people I see write the most appalling code I've ever seen. I think it has something to do with the fact that the science people don't pretend to know everything and are much more willing to learn something new while the IT people already know everything.
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I just saw The Measure of a Man episode on the Star Trek Labor Day marathon. Data has a speed of 60 Teraflops and 100 petabytes of storage. That used to seem large in the late 1980s. (Episode were Data goes on trial whether he is a machine or sentient.)
It will not run 32 bit linux, so of course, the admins in charge are going to bitch about the lack of adobe flash support.
What are we going to do tonight Brain?
Yeah, that was my thought. Roadrunner at Los Alamos sits at the top of the 500 list with Rmax 1,026,000. I don't know enough about benchmarks to distinguish between "Rmax" and "sustained petascale," but it is achieving over a petaflop. Maybe someone here can tell us more about linpack vs. whatever they're using for this new one. I notice the article linked in the story mentions Roadrunner at the end, but without saying how it compares in speed. It doesn't seem to say by what specific measure this new computer's speed surpasses a petaflop.
Can anyone tell me how to set my sig on Slashdot?
...Apple used to use a Cray to design their new computers, whereas Seymoure Cray used an Apple to design his.
More compute power is nice, but only if the programs are making efficient use of it. MPI is not a particularly efficient method of message passing, and many implementations (such as MPICH) are horribly inefficient implementations. Operating systems aren't exactly well-designed for parallelism on this scale, with many benchtests putting TCP/IP-based communications ahead of shared memory on the same fripping node! TCP stacks are not exactly lightweight, and shared memory implies zero copy, so what's the problem?
Network topologies and network architectures are also far more important than raw CPU power, as that is the critical point in any high-performance computing operation. Dolphinics is quoting 2.5 microsecond latencies, Infiniband is about 8 microseconds, and frankly these are far far too slow for modern CPUs. That's before you take into account that most of the benchmarks are based on ping-pong tests (minimal stack usage, no data) and not real-world usage. I know of no network architecture that provides hardware native reliable multicast, for example, despite the fact that most problem-spaces are single-data, most networks already provide multicast, and software-based reliable multicast has existed for a long time. If you want to slash latencies, you've also got to look at hypercube or butterfly topologies, fat-tree is vulnerable to congestion and cascading failures - it also has the worst-possible number of hops to a destination of almost any network. Fat-tree is also about the only one people use.
There is a reason you're seeing Beowulf-like machines in the Top 500 - it's not because PCs are catching up to vector processors, it's because CPU count isn't the big bottleneck and superior designs will outperform merely larger designs. Even with the superior designs out there, though, I would consider them to be nowhere even remotely close to potential. They're superior only with respect to what's been there before, not with respect to where skillful and clueful engineers could take them. If these alternatives are so much better, then why is nobody using them? Firstly, most supercomputers go to the DoD and other Big Agencies, who have lots of money where their brains used to be. Secondly, nobody ever made headlines off having the world's most effective supercomputer. Thirdly, what vendor is going to supply Big Iron that will take longer to replace and won't generate the profit margins?
(Me? Cynical?)
It's a small world and it smells funny; I'd buy another if it wasn't for the money; Take back what I paid (SoM)
The amount of porn you can download with this thing? Isn't that the number one thing the computer has evolved to?
Anything and Everything about the Net
in 40 years some kid will laugh at your pathetic attempt at geek coolness when you mention the Bluewater and say "wow your old, Im amazed anyone needed a warehouse just for one petaflop even my Wango-matic game cube has 50 petaflops"
Folding @ Home easly trounces this puny supercomputer.
Nah but it will finally run Vista.
"So long and thanks for all the fish."
in 40 years some kid will laugh at your pathetic attempt at geek coolness when you mention the Bluewater and say "wow your old..."
Forty more years of the kids saying "your"? Kill me now! :)
Blue Waters will be the first to deliver a sustained petaflop on "real-world" applications, meaning various scientific simulations. Specifically, the program solicitation required prospective vendors to explain how their proposed systems would sustain a petaflop on three types specific types of simulations, one each in turbulence, lattice-guage quantum chromodynamics, and molecular dynamics.
Granted, Roadrunner was the first machine to deliver a petaflop on the Linpack benchmark (though certainly IBM's own implementation of it). The benchmark does nothing more than set up and solve a system of linear equations. Roadrunner solved a system of 2,236,927 equations (in other words, it had a 2,236,927-by-2,236,927 coefficient matrix) in 2 hours.
But Blue Waters is planned to deliver a petaflop on applications that normally don't sustain >80% of theoretical peak; these applications are lucky to get near 20%.
2020 seems unlikely. A reasonably accurate real-time synaptic simulation can run maybe 100 neurons on a high end pc today, probably less. A human brain has about 100 billion neurons, so we're 1 billion times short in computation. Last time I checked, GPUs had not yet been used in neuron simulation, so I'll even give you that we may be 1000 times better off. That's still 1 million X improvement needed to match the brain, or roughly 20 more generations of computer hardware, at a generous 18 months, that leaves us at 30 years, 2038.
I will be seriously surprised if an even vaguely accurate simulation of the human brain is running before 2050.
"Who is the Journal of Quantum Physics going to believe?" --Stephen Hawking
Simulating nuclear explosions.
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