Japan's Petaflop Supercomputer
slashthedot writes "Japan has built the fastest supercomputer in the world. While the BlueGene/L contains 130,000 processors, Japan has managed to create the first Petaflop supercomputer, called MDGrape-3, with just 4808 chips, and it cost just $9 million to develop."
It now costs 15 dollars per gigaflop. In the early 90s, a million dollars per gigaflop was normal.
Religion for nerds. Stuff that really matters
The original article seems to be unreachable, so I can't read it, but the precis has the wrong chip count: It does have 4808 LSI chips, but it also has 19,122 Xeon processors.
The Cell processor can do ~200 GFLOPS - not IEEE quality FLOPS however, however they're 'good enough single precision FLOPs' for it's target uses. This is probably why this new supercomputer won't get into the Top500 list, because it's very specialised and thus probably nowhere near as good at IEEE conformant calculations.
The Cell processor is not running at 200GHz. There's this concept called 'parallelisation', it's how your graphics card can do dozens, if not hundreds, of operations per clock cycle. In Cell's case it can do 8 (number of SPUs) * 4 (128-bit registers, SIMD) * 2 (units) = 64 SP FLOPS per clock cycle, and that's not including the PPU which has VMX128 and an FPU itself.
However make the Cell processor calculate IEEE conformant FLOPS, and it gets a double precision score of around 20GFLOPS. Still good though.
The above was from memory, details may vary, figures are roughly correct, YMMV, etc.
"Show me the MFlops/Watt rating of this?"
No problemo!
The number of flops: (10 ^ 15) / 4808 = about 207,986,688,852 flops per chip, - from a previous poster.
The number of watts: 300,000 - from the manufacturers' site = 62 watts/chip
207,986,688,852 / 62 = 33,546,240 flops (33 MFlops) / watt.
Well the examples that you mention are not really the same as "attempting to break software and search for problems long before release." If I understand these issues correctly: (1) (with apologies to crypto specialists) RC5 cracking required lots of CPU time to factor a big-ass number, (2) projects like Folding@Home aren't "looking for a cure for cancer," they're running (I think) quantum chemistry simulations to find out how certain molecules can act in certain situations, and (3) SETI@Home is looking for specific patterns in signal data. In all three of these cases, there's a few common (maybe not so simple) operations that need to be applied to a large set of data or initial conditions, and that's why they need lots of machines, or fast machines.
Figuring out how clever people will take advantage of a particular implementation of a web browser or TCP/IP stack is a completely different class of problem IMHO. Yeah, maybe there's some clever AI techniques that may simulate attack attempts, and maybe they could come up with attacks that nobody has thought of yet, but a really fast computer will not somehow magically solve these kinds of problems for us. There's a lot of hard science and software engineering that needs to be done first.
[b.belong('us') for b in bases if b.owner() == 'you']
Quoting another link you can see how they reached these numbers (which I take issue with):
- http://mdgrape.gsc.riken.jp/modules/tinyd0/index.
With that answered, I'm confused. Another poster sent along that link which explains what Riken will do. I'm confused about that actually. Reading the page, based on the verb usage, either someone didn't understand future and past tense (possible, but unlikely), or they haven't built the entire box yet. Perhaps I'm reading a bit too much into it... it's quite possible that someone simply hasn't updated the website.
Based on the webpage, all of the calculations to reach 1 petaflop are based on theoretical peak performance measurements, extrapolated from the theoretical peak of a single special-purpose ASIC which has been built, but may or may not have been actually placed into a fully configured system. Nothing talks about measured benchmarks, and the OP's article contains the same theoretical extrapolated numbers.
Anyone know if they've actually built it?
~ Mike
Michael C. Hollinger
The problem with that is that this computer is very specialised to molecular simulations. It can't very easily do other things, like seti or folding (okay, well, maybe that it can do). It was easy to design and cheap because it didn't have to be general purpose and adaptable, like BlueGene/L is.
I love deadlines. I like the whooshing sound they make as they fly by. - Douglas Adams