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Titan Tops Top500 Supercomputing List

miller60 writes "The new Top500 list of the world's most powerful supercomputers is out, and the new champion is Titan, the new and improved system that previously ruled the Top500 as Jaguar. Oak Ridge Labs' Titan knocked Livermore Labs' Sequoia system out of the top spot, with a Linpack benchmark of more than 17 petaflops. Check out the full list, or an illustrated guide to the top 10."

6 of 52 comments (clear)

  1. I'm looking forward to the.. by mrbluze · · Score: 4, Funny

    2013 Calendar full of naked supercomputers displaying their petaflops!

    --
    Do it yourself, because no one else will do it yourself. [beta blockade 10-17 Feb]
  2. My previous place of employment - #71 by Cutting_Crew · · Score: 3, Informative

    NASA/Stennis Space Center, Mississippi. Used to be in the top 10. they have fallen way behind.

  3. Redudundant expression by Anonymous Coward · · Score: 4, Informative

    Sorry to be pedantic, but "petaflops a second" is redundant -- FLOPS means "floating-point operations per second."

  4. That's some accelleration... by eth1 · · Score: 4, Funny

    more than 17 petaflops a second.

    Wait... 17 petaflop per second per second?! How long can it keep that up?

  5. Re:Obligatory by cashman73 · · Score: 4, Informative

    This is significant, because if you look at the list, Titan only has about 500,000 cores, versus 1.5 million cores on Sequoia. The overall increase in peta-FLOPS isn't that much, but the fact that Titan did this with only about 1/3 the cores as Sequoia IS significant.

  6. Re:And The software is??? by Anonymous Coward · · Score: 3, Informative

    It ships with Compute Node Linux, which is a cut down (lower overhead) version of SLES. It supports several schedulers, but ORNL typically uses Altair PBS on the big systems (http://www.cray.com/Products/XK/Software.aspx). ORNL provides a large number of compilers and libraries that users can use in the form of 'modules' (http://www.olcf.ornl.gov/support/user-guides/titan-user-guide/). And in terms of scheduling/partitioning, the user just requests a specific number of nodes when they submit a job, and they get those nodes to themselves for the allotted time. It's pretty low-impact on the compute nodes, and less exciting than you might think. They don't put much emphasis on the software when reporting on these machines, because it's stripped down as much as possible to allow the user applications to run at peak performance.