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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."
Weather modeling comes to mind, both terrestrial and space.
rj
These machines are used to work on simulations that involve aerodynamics and hydrodynamics, quantum electrodynamics (QED), or electromagnetohydrodynamics. All of these simulations require that a mathematical model is constructed from a high density mesh of data points (2048 ^ 3). Blocks of such points are allocated to individual processors. Because of this, each processor must be able to communicate at a high speed with its neighbours (up to 26 neighbours with a cubic mesh).
Usually, the actual individual calculations per element will be take up less than a page of mathematical equations, but require high precision, so the data values will be 64-bit floating point quantities. A single element might require 20 or more variables. Thus the need for some many processors and high clock speed.
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Do you notice neither USA or Russia blows a portion of planet to test nuclear weapons anymore? It is because the planet is so peaceful so further research is not required? Unfortunately no.
These monsters can simulate a gigantic nuclear explosion in molecular level.
Or for peace purposes, they can actually simulate that New Orleans storm based on real World data and pinpoint exactly what would happen.
Considering that we've got SDR IB with under 2 microseconds latency for the shortest hops (and ~3 for the longest), I think you need to go update your anti-cluster argument. :) The problems with congestion in fat trees have virtually nothing to do with latency. Yes massive congestion will kill your latency numbers, but given that you don't get cascades and other failures causing congestion without fairly large bandwidth utilization, latency is the least of your worries that that point. Furthermore, the cascades you talk about also aren't common except in extremely oversubscribed networks or in the presence of malfunctioning hardware. We do our best to use properly functioning hardware and to have no more that 2:1 oversubscription (with our largest machine not being oversubscribed at all).
MPICH ain't that bad (heck, MPICH2, even just it's MPI-1 parts might be considered to be pretty good by some). MPI as standard for message-passing is fine. I'd love to hear what you think is wrong with MPI and see some examples where another portable message passing standard does consistently better. Though it's a bit like C or C++ or Perl in that there are lots of really bad ways to accomplish things in MPI and a handful of good ones. It's low-level enough that you need to know what you're doing. But if you believe anyone that tells you they have a way to make massively parallel programming easy, I've got a bridge you might be interested in.
Finally, I don't know of much in the way of a "supercomputer" that's using TCP for it's MPI traffic these days, so you can put that old saw out to pasture as well.
Yes...I am a rocket scientist.
I'm working on a PhD in chemical engineering, and I do simulations. I occasionally use Lonestar and Ranger, which are clusters at TACC, the U. of Texas' supercomputing center. Lonestar is capable of around 60 TFLOPS and Ranger can do around 500-600 TFLOPS. A few users run really large jobs using thousands of cores for days at a stretch, but the majority of people use 128 or fewer cores for a few hours at a time.
My research group does materials research using density function theory, which is an approximate way of solving the Schroedinger equation. Each of our jobs usually uses 16 or 32 cores, and takes anywhere from 5 minutes to a couple of days to finish. Usually we are interested in looking at lots of slightly different cases, so we run dozens of jobs simultaneously.
The applications are pretty varied. Some topics we are working on -
1) Si nanowire growth
2) Si self-interstitial defects
3) Au cluster morphology
4) Catalysis by metal clusters
5) Properties of strained semiconductors