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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?"

7 of 417 comments (clear)

  1. What is the stumbling block? by Dancin_Santa · · Score: 5, Insightful

    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)?

    1. Re:What is the stumbling block? by anon+mouse-cow-aard · · Score: 4, Insightful

      Thought experiment: Order 10000 PC's. time how long it takes to get them installed, with power, network cabling, and cooling, in racks, and installed with the same OS.

      Second thought experiment. Imagine the systems are built out of modular bricks that are identical to deskside servers. so that they can sell exactly the same hardware in anywhere from 2 to 512 processors by just plugging the same standard bricks together, and they all get the same shared memory, and run one OS. Rack after rack after rack. That is SGI's architecture. It is absolutely gorgeous.

      So they install twenty of the biggest boxes they have, and network those together.

      $/buck ? I dunno. Is shared memory really a good idea? Probably not. but it is absolutely gorgeous, and no-one can touch them in that shared memory niche that they have.

    2. Re:What is the stumbling block? by Geoff-with-a-G · · Score: 4, Insightful

      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?

      Well, are we talking about actual supercomputers, not just clusters? 'Cause if you're just trying to break these Teraflops records, you can just cram a ton of existing computers together into a cluster, and voila! lots of operations per second.

      But it's rare that someone foots the bill for all those machines just to break a record. Los Alamos, IBM, NASA, etc. want the computer to do serious work when it's done, and a real supercomputer will beat the crap out of a commodity cluster at most of that real work. Which is why they spend so much time designing new ones. Because supercomputers aren't just regular computers with more power. With an Intel/AMD/PowerPC CPU, jamming four of them together doesn't do four times as much work, because there's overhead and latency involved in dividing up the work and exchanging the data between the CPUs. That's where the supercomputers shine: in the coordination and communication between the multiple procs.

      So the reason so much time and effort goes into designing new supercomputers is that if you need something twice as powerful as today's supercomputer, you can't just take two and put them together. You have to make new architecture that is even better at handing vast numbers of procs first.

  2. Re:Ok, what is the point of this? by servognome · · Score: 4, Insightful

    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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  3. it's the wetware by Doc+Ruby · · Score: 4, Insightful

    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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  4. Re:hmmmm...... by Shag · · Score: 4, Insightful
    "...with Columbia, scientists are discovering they can potentially predict hurricane paths a full five days before the storms reach landfall."

    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."

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    Village idiot in some extremely smart villages.
  5. Re:Read on to the next paragraph by RageEX · · Score: 5, Insightful

    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.