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25th TOP500 List Released
Chris Vaughan writes "The 25th edition of the TOP500 list of the world's fastest supercomputers was released today (June 22, 2005) at the 20th International Supercomputing Conference (ISC2005) in Heidelberg Germany. The No. 1 position was again claimed by the previously mentioned BlueGene/L System. At present, IBM and Hewlett-Packard sell the bulk of systems at all performance levels of the TOP500. The U.S is clearly the leading consumer of HPC systems with 294 of the 500 systems installed there (up from 267 six months ago)."
The list can be found here:6
http://www.top500.org/lists/plists.php?Y=2005&M=0
You'd think that it would be a good idea to actually link to the html list, or the xml list, or the pretty charts.
The press release is interesting too.
Karma: SELECT `karma` FROM `users` WHERE `userid`=138474;
It would be great if we could verify Moore's law through some simple stats using the histrical data from this Top500 list.
-For example:How many years did it take for Number ones on average to be dropped off the 500 list?
- How many years after the list was published did it take personal computers tu make it in the 500list? To make it to the number 1 spot?
- How many transistors did these computers have? Did it verify Moore's law?
- Are we getting more TFLOPS per watt now? Per transistor?
etc..
Artificial intelligence is no match for natural stupidity
And at position #501, OSX running on an Intel processor. Hey, Steve promised it would be fast.
"It's the height of ridiculousness to say for those 9 lines you get hundreds of millions."
What's surprising to me is that Cray used to be synonymous with supercomputers and they now have comparatively few entries.
MareNostrum wins hands down for best looking computer room/
I've abandoned my search for truth; now I'm just looking for some useful delusions.
It all depends on the system architecture and the type of problem being solved. Certain problems will adhere better to certain architectures and thus allow for a smaller gap between the theoretical and actual performance. The gaps can also be inherent in the architecture itself (e.g. communications bandwidth like you said).
Personally, I don't think that Human brains are binary based, logic gate controlled computation machines, and this difference accounts for why we have so much diffuclty with developing strong AI on them.
I do believe, however, that we will eventually "crack the code" to the fundamental archetecture of our brains, and once we do that, we will re-design our computers accordingly, and finally achieve strong AI.
I also believe, that our currently architected computers will play a key role in assisting us with cracking this code.