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Comments: 64 +- Technology: Modeling Supernovae With a Supercomputer on Sunday May 04 2008, @10:14AM
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A team of scientists at the University of Chicago will be using 22 million processor-hours to simulate the physics of exploding stars. The team will make use of the Blue Gene/P supercomputer at Argonne National Laboratory to analyze four different scenarios for type Ia supernovae. Included in the link is a video simulation of a thermonuclear flame busting its way out of a white dwarf. The processing time was made possible by the Department of Energy's INCITE program.
"Burning in a white dwarf can occur as a deflagration or as a detonation. 'Imagine a pool of gasoline and throw a match on it. That kind of burning across the pool of gasoline is a deflagration,' Jordan said. 'A detonation is simply if you were to light a stick of dynamite and allow it to explode.' In the Flash Center scenario, deflagration starts off-center of the star's core. The burning creates a hot bubble of less dense ash that pops out the side due to buoyancy, like a piece of Styrofoam submerged in water."
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with a computer? (Score:4, Funny)
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Kaboom (Score:1)
like a piece of Styrofoam submerged in water
Now I know what to do with myself on this slow Sunday morning.
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They need to get Michael Bay involved.. (Score:1, Funny)
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crysis (Score:1)
it would be interesting....... (Score:1)
Modeled it at home for forty-seven cents... (Score:2)
There seems to be some quantum effect component also, because right after the simulation, my landlady appeared and went supernova too!
saw this on tv (Score:3, Informative)
honest question (Score:1)
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BTW, 22 million hours = 2500 years, not 42 years.
Re:honest question (Score:4, Informative)
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!news (Score:2, Interesting)
So.... (Score:1)
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Computing in Cloud (Score:3, Informative)
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Architecture, language, details? (Score:1)
Re:Architecture, language, details? (Score:4, Informative)
A study of parallel techniques for visualisation [ucdavis.edu].
A parallel visualization pipeline for Terascale earthquake simulation [ucdavis.edu]
Scientific Discovery through Advanced Visualization [ucdavis.edu]
A case study in Supernovae Simulation Data [uchicago.edu]
It's just amazing to find out how much is going on inside a star - not just the fusion of Hydrogen and Helium atoms, but intense magnetic fields that drive rivers of liquid Hydrogen and Helium through rising and falling convection cells, which in turn create new magnetic fields.
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Re:Architecture, language, details? (Score:4, Informative)
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p.s. - i'm one of the original authors of the flash code.
Use Those Excess Cycles (Score:2)
We just need continually improving ways to make those excess cycles available.
Superfluous Supercomment (Score:1)
with a Supercomputer? (Score:1)
Every so often the star seems to... (Score:2)
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Re:flawed (Score:5, Informative)
Simulation is something which simulates a system or environment in order to predict actual behavior.
To speculate on the other hand is to make an inference based on inconclusive evidence; to surmise or conjecture.
So, he was indeed insightful when he stated that the lack of understanding would render the results speculative at best.
(all definitions courtesy of wikitionary)
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Re:flawed (Score:5, Interesting)
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How is that not just hair splitting semantics?
Re:flawed (Score:5, Insightful)
In building a computer model/simulation, you generally follow these steps:
1) problem formulation - what do you want to figure out, gather data, get the "reference behavior pattern"
2) formulate a mental model of the system - what are the entities involved and how are they related
3) build and debug your model
4) verification - this is where you ensure the model behaves as expected against specific sets of inputs - as you change inputs, does it do what you expect (I turn up the volume knob - and the sound gets louder)
5) validation - this is where you compare the results of the model with the reference data from the real world. If it doesn't match, you then have to back up and figure out what's wrong... was the implementation of the model incorrect? were your initial hypotheses incorrect? And if it does match, have you gathered enough real world data to know your model is functioning well? How confident are you of this model's ability to model the system you're interested in.
So suppose you've built a model that you can validate against gathered data, you still have to demonstrate that your model is valuable to the scientific community.
You're probably going out on a limb to make strong assertions when a model demonstrates/predicts behavior that has not been observed. However, it can serve a great role in helping determine what other things to look for, what conditions may exist, or help see relationships that you may not have seen before.
The controversy is over how much you can use a model to help prove a hypothesis.
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Pfft (Score:1)
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Re:flawed (Score:5, Informative)
we understand little about it and the math formula used will be a half guess. supercomputer or not, results will be speculative at best.
I don't think you understand how experiments work... If the results of the computations are something other than what is observed in nature, then the methods and/or equations are proven wrong. That is most certainly a NON-speculative result.
Just because the model shows a burst of star stuff blowing out this way or that way in some particular configuration doesn't mean that scientists will leap up from their chairs and say "Stars do this, and we've proven it."
You can never know if your models are correct. All you can do is continually test them and try to prove them wrong. Maxwell's equations have not been proven to be correct -- they've just never been shown to be wrong. This simulation is just a step on the path of evidence.
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"I don't think you understand how experiments work" sounds like you are making an assumption as well
I'm not assuming anything. I've formed a model based on the evidence.
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we understand little about it and the math formula used will be a half guess. supercomputer or not, results will be speculative at best.
There is a big difference between guessing at some thing and hoping for the best, verses a systematic analysis of a problem using all the available knowledge that man has right now. Yeah, sounds like a sugar coating on exactly the same thing but come on and think about it. Science is mix a little ingenuity in with previously known facts and a healthy dose of self cynicism. It's the self defeatist attitude like this that hampers progress.
Not to mention several "PhD life spans" probably were spent on e
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"The Argonne Blue Gene/P supercomputer is one of the largest and fastest supercomputers in the world," said Fisher, a Flash Center Research Scientist. "It has massive computational resources that are not available on smaller platforms elsewhere." Desktop computers typically contain only one or two processors; Blue Gene/P has more than 160,000 processors. What a desktop computer could accomplish in a thousand years, the Blue Gene/P supercomputer can perform in three days.
Oh wait ...