FASTRA II Puts 13 GPUs In a Desktop Supercomputer

An anonymous reader writes "Last year tomography researchers of the ASTRA group at the University of Antwerp developed a desktop supercomputer with four NVIDIA GeForce 9800 GX2 graphics cards. The performance of the FASTRA GPGPU system was amazing; it was slightly faster than the university's 512-core supercomputer and cost less than 4000EUR. Today the researchers announce FASTRA II, a new 6000EUR GPGPU computing beast with six dual-GPU NVIDIA GeForce GTX 295 graphics cards and one GeForce GTX 275. The development of the new system was more complicated and there are still some stability issues, but tests reveal the 13 GPUs deliver 3.75x more performance than the old system. For the tomography reconstruction calculations these researchers need to do, the compact FASTRA II is four times faster than the university's supercomputer cluster, while being roughly 300 times more energy efficient."

Comments

Awesome

[enderjsv]

Almost meets the minimum requirements for Crysis 2

Re:How fast is this really?

[jandrese]

If you read the article it tells you that the supercomputer has 256 Opteron 250s (2.4Ghz) and was built 3 years ago. If you have a parallizable problem that can be solved with CUDA, you can get absolutely incredible performance out of off-of-the-shelf GPUs these days.

Re:GPU accuracy

[kpesler]

Presently the G200 GPUs in this machine support double-precision, but at about 1/8 the peak rate of single-precision. In practice, since most codes tend to be bandwidth limited, and pointer arithmetic is the same for single and double precision, double-precision performance is usually closer to 1/2 that of single-precision performance, but not always. With the Fermi GPUs to be released early next year, double-precision peak FLOPS will be 1/2 of single-precision peak, just like on present X86 processors. Also note that many scientific research groups, such as my own, have found that contrary to dogma, single-precision is good enough for most of the computation, and that a judicious mix of single and double-precision arithmetic gives high-performance with sufficient accuracy. This is true for some, but not all, computational methods.