Slashdot Mirror
Petaflops? DARPA Seeks Quintillion-Flop Computers
coondoggie writes "Not known for taking the demure route, researchers at DARPA this week announced a program aimed at building computers that exceed current peta-scale computers to achieve the mind-altering speed of one quintillion (1,000,000,000,000,000,000) calculations per second. Dubbed extreme scale computing, such machines are needed, DARPA says, to 'meet the relentlessly increasing demands for greater performance, higher energy efficiency, ease of programmability, system dependability, and security.'"
Call me tinfoil hat wearer, but me thinks they want a faster way of cracking encryption...
Quintillion is not an SI prefix. The next step after Peta is Exa.
The Tao of math: The numbers you can count are not the real numbers.
They come up with ideas that only ultra-geeks and science fiction nerds could come up with, and then they get billions in funding for it! It's like paradise. The fact that they're actually successful at advancing human technology is just icing on the cake.
Right. If you actually read the announcement, it's not that they want yet more boondoggle supercomputing centers. What they want is more crunch power in small boxes. Read the actual announcement (PDF). See page 17. What they want is 1 petaflop (peak) in one rack, including cooling gear. The rack gets to draw up to 57 kilowatts (!).
Simulating exploding hydrogen bombs, weather simulation, brute-force cracking, etc. Basically any distributed project you can think of (see BOINC) can also be done with a supercomputer.
It's a scientific model with a boatload of variables and dependencies. Ask these guys.
There are broad classes of algorithms where you can make good use of essentially arbitrary amounts of computing power to get better answers. When doing physical simulations of something like airflow over a jet wing, or the movement of a weather system, or the explosion of a hydrogen bomb, you'll break everything up into tiny units that you treat as monolithic elements whose behavior can be treated relatively simply, and calculate what happens to them over some tiny timescale, call the result the new state of the universe, and repeat. This is called "finite element analysis".
Because you're calculating everything in discreet steps, though, errors creep in and accumulate. The more processing power you have, the more elements you can use and the smaller time scales you can calculate over and get a more accurate answer in the same amount of time. The reason it's unacceptable to do the same calculation but have it go 1,000 or 1,000,000 times slower is that these simulations might already take hours, days, weeks, or even longer. Even the longest DoD contract needs an answer to the behavior of a proposed jet fighter wing in less than 1,000,000 days. :)
Scientific computing is an area where there will always be a use for more processing power.
There are other areas where it can be important, when you have real time constraints and can't just reduce your accuracy to make it work. I recall a story from advanced algorithms class where a bank was handling so many transactions per day that the time it took to process them all was more than 24 hours. Obviously this was a problem. The solution in that case was to modify the algorithm, but that's not always possible, and you need more computing. This is a little different in that you need the extra power to allow growth, as opposed to science where you could hand them an exaflop computer today and they'd be able to use it to its fullest.
The enemies of Democracy are