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How To Build a Supercomputer In 24 Hours 161

An anonymous reader writes with a link to this "time lapse video of students and postdocs at the University of Zurich constructing the zBox4 supercomputer. The machine has a theoretical compute capacity of ~1% of the human brain and will be used for simulating the formation of stars, planets and galaxies." That rack has "3,072 2.2GHz Intel Xeon cores and over 12TB of RAM." Also notable: for once, several of the YouTube comments are worth reading for more details on the construction and specs.
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How To Build a Supercomputer In 24 Hours

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  • by Grumpinuts ( 1272216 ) on Sunday November 04, 2012 @12:43PM (#41872993)
    Used to do this kind of stuff when I was with IBM about 10 years ago, we had a group in XSeries Manufacturing who specialised in quick turnaround configuration of HPC rack systems just like this. Funnily enough, one of the major logistical elements was dunnage, ie the empty cardboard/foam and plastic that all the option parts arrive in. When running full out we used to have 1-2 guys per shift just to move the rubbish out to the big compactors out back. You wouldn't believe just how much packaging even a comparatively small cluster like that can generate.
  • Re:Pretty sure (Score:4, Interesting)

    by __aaltlg1547 ( 2541114 ) on Sunday November 04, 2012 @01:22PM (#41873265)

    Google's cars say different.

    Looking at physical complexity:
    A human brain has about 86 billion neurons. An Intel Core-i7 process has 731 million transistors. A neuron is more complex than a transistor. Let's say it does a job, for the sake or argument, that would take about 16 transistors. So say the Core-i7 has the equivalent of about 45 million neuron-equivalents. That's a factor of about 1900 in physical complexity.

    But the brain manages to pull off a clock cycle about 200 Hz, based on the neuron's firing rate. Maybe 1000 Hz at most. The clock rate of the CPU is 3.2 GHz. It is 16 million times faster than your brain.. Since the computer can execute programs of arbitrary complexity, it can simulate your brain's operation -- if properly programmed, with a much smaller hardware set running much faster. In raw computational capacity, it apparently has 16 million / 2000 = 8000 times the computational capacity of your brain. So even if its' simulation were quite computationally inefficient, it should still be able to do the job of a number of brains, if programmed to do so.

    In short, exceeding the capacity of a human brain isn't a hardware problem any more. It hasn't been for years. It's a programming exercise, albeit a particularly challenging one.

All seems condemned in the long run to approximate a state akin to Gaussian noise. -- James Martin

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