SGI & NASA Build World's Fastest Supercomputer
GarethSwan writes "SGI and NASA have just rolled-out the new world number one fastest supercomputer. Its performance test (LINPACK) result of 42.7 teraflops easily outclasses the previous mark set by Japan's Earth Simulator of 35.86 teraflops AND that set by IBM's new BlueGene/L experiment of 36.01 teraflops. What's even more awesome is that each of the 20 512-processor systems run a single Linux image, AND Columbia was installed in only 15 weeks. Imagine having your own 20-machine cluster?"
Why does it take so long to build a super computer and why do they seem to be redesigned each time a new one is desired?
It's a little like how Canada's and France's nuclear power plant system are built around standardized power stations, cookie cutter if you will. The cost to reproduce a power plant is negligble compared to the initial design and implementation, so the reuse of designs makes the whole system really cheap. The drawback is that it stagnates the technology and the newest plants may not get the newest and best technology. Contrast this with the American system of designing each power plant with the latest and greatest technology. You get really great plants each time, of course, but the cost is astronomical and uneconomical.
So to, it seems with supercomputers. We never hear about how these things are thrown into mass production, only about how the latest one gets 10 more teraflops than the last and all the slashbots wonder how well Doom 3 runs on it or whether Longhorn will run at all in such an underpowered machine.
But each design of a supercomputer is a massive success of engineering skill. How much cheaper would it become if instead of redesigning the machines each time someone wants to feel more manly than the current speed champion, that the current design be rebuilt for a generation (in computer years)?
Really, given the fact that most popular computers have enough processing power to handle anything, and the fact that clustering technology has evolved and is usable in case they aren't...what is the point in the "super computer"?
The super computer is a cluster (10k+ processors in 20 nodes).
Not all applications/computations scale by just adding computers to the cluster.
An example would be solving for z: x=84+19, y=5*3, z=x+y
The ultimate solution z is limited by the speed x & y can be solved. You can have an individual computer solve for x and another for y in parallel. But no matter how many more computers you add, none of them can solve z until x&y are solved first, and none of them would speed up the computation of x&y.
After a certain scale, you do not get benifits of parellel processing, so the only way to speed things up is to make each individual computer faster.
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Weather prediction, it turns out, is *not at all* like playing chess. Chess is a deterministic linear process operating on rigid, unchanging rules. There is always a "best move" for every board state, which a sufficiently fast and capacious database could search for. Weather is chaotic, a nonlinear process. It feeds back its state into its rules, in that some processes increase the sensitivity to change of other simultaneous processes. Chaos cannot be merely "solved", like a linear equation; it must be simulated and iterated through its successive states to identify more states.
Of course, we're just getting started with chaos dynamics. We might find chaotic mathematical shortcuts, just like we found algebra to master counting. And studying weather simulation is a great way to do so. Lorenz first formally specified chaos math by modeling weather. While we're improving our modeling techniques to better cope with the weather on which we depend, we'll be sharpening our math tools. Weather applications are therefore some of the most productive apps for these new machines, now that they're fast enough to model real systems, giving results predicting not only weather, but also the future of mathematics.
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make install -not war
You don't live somewhere that gets hurricanes, do you? 'Cause scientists can already "potentially predict hurricane paths a full five days before the storms reach landfall." Hell, I can do that. A freakin' Magic 8 Ball can potentially do that.
Maybe they're trying to say something about doing it with a better degree of accuracy, or being right more of the time, or something like that, but it doesn't sound like it from that quote.
"Hey, guys, look at this life-sized computer-generated stripper I'm rendering in real-ti... oh, what? Um, tell the reporter we think it'd be good for hurricane prediction."
Village idiot in some extremely smart villages.
Good job NASA? Yeah I'd agree. But what about good job SGI? Why does SGI always seem to have bad marketing and not get the press/praise they deserve?
This is an SGI system. SGI has laid out plans for terascale computing (stupid marketing speak for huge ccNUMA systems) a while ago. I'm sure NASA and SGI worked together but this is essentialy an 'Extreme' version of an off-the-shelf SGI system.