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TeraGrid Gets an Upgrade
The Fun Guy writes to tell us The NSF has awarded $48 million to the University of Chicago to operate and expand TeraGrid over the next five years. TeraGrid is 'a national-scale system of interconnected computers that scientists and engineers are using to solve some of their most challenging problems. TeraGrid is the world's largest open computer, storage and networking system. Only the U.S. Department of Energy's weapons laboratories have larger systems, which are dedicated to classified research.' Currently, the TeraGrid's power is just over 60 teraflops.
Does it run Linux? Oh, I see it does... nevermind.
I like it - maybe they can define PI down to an even greater degree. !!
...stack against the likes of distributed.net and other similar projects for processing power?
Unpleasantries.
but only if it comes in white....
When the posters fear their moderators, there is tyranny; when the moderators fears the posters, there is liberty.
A good slashdotting should be just what they want to test their servers.
yes
I wonder when the cluster discovers it's own existance and deticates that there is no need for the human race.
...Windows Vista!!
Had to say it, sorry!
please excuse my apathy
...giving a whole new meaning to Teraflops.
"Made up/misattributed quote that makes me look smart. I am on
hah .. you could just put 60 xbox 360s together to achieve that kind of power ..
xbox 360 specs
...you know, developing sources of energy.
it makes me smile.
... cool.
... the people of Slashdot!)
It's just so
(And the only people who I say that to are my research group members and
The TeraGrid is well managed too.. very few problems for such a huge system.
Favorite
One paper which might help point in the right direction is "Isoefficiency: Measuring the Scalability of Parallel Algorithms and Architectures" by Grama, Gupta, Kumar. You pose a very interesting question. Any application where you have a large number of steps, each step relying upon the result from the previous step, and each step independently not parallelizable would probably fit your description. I don't know of anything off the top of my head where you couldn't parallelize some portion of it, but it is much easier to think of applications which cannot scale to large levels of parallelism. The trivial examples of good scalability like rendering frames of movies or SETI@home will scale to any cluster or set of PC's you put them on. Other things like large matrix multiplications or FFTs or N-body problems do not scale as well. In these cases as you subdivide the problem into smaller pieces for your larger number of machines, the computation on each processor will quickly become small while the communication between processors will become more significant. I guess the Alpha-Beta searches will probably not benefit by parallelization as one might imagine. You could do some proof that although you can evaluate more nodes in the game-tree, you cannot prune, and thus your search will degrade towards a parallelized MinMax search.
I have a non-parallelizable algorithm for you. Apply a non-associative operation to elements of an array like this:
result = (a[0] * (a[1] * (a[2] * (a[3] *(....)))))
Note that I use * to represent some binary operator that satisfies non-associativity. I think that this algorithm may be provably non-parallelizable, since the innermost * operation must be performed before any other * operations. Thus no two * operations can be done at the same time, and thus none of the * operations can be parallelized. Furthermore if these are the only operations being performed in the entire algorithm, then no operations in the algorithm can be parallelized. Thus the algorithm is non-parallelizable by any reasonable definition. I do assume for this proof that you cannot parallelize the * operator.
On a side note, I could also prove that NP hard problems are still NP hard on even a large number of processors.