i have read that there were 100X acceleration on certain problems when you use NVIDIA GPU instead of CPU.
what are the best performance acceleration timings using cuda on different problems.
please state the problem and the acceleration factor along with links for papers if possible.
views:
298answers:
2
+3
A:
These are a few striking examples from natural sciences:
Ab initio quantum chemistry calculation (TeraChem): up to 50x
Molecular dynamics simulations (HOOMD): up to 32x
Molecular orbitals visualization with VMD: 20x-100x
More could be found here:
http://www.nvidia.com/object/tesla_bio_workbench.html
Papers are to be found within the link. Unfortunately I could not show
more direct links, since my status (new account) does not permit more than
one hyperlink.
Thanks.
artaak
2010-03-10 20:03:34
I would take those numbers with a grain of salt. The most glaring omission - single precision versus double precision on CPU, which for many applications makes results suspect at best
aaa
2010-03-11 18:48:12
Agreed. Not that I advocate for a single precision: However, a general criticism has to be strengthened by concrete examples where single precision does not work. After all, the floating point addition is not an associative operation - in any parallel execution context it matters A LOT.
artaak
2010-03-12 00:08:51
my background is chemistry, where accuracy must be `10^-8 `. For such applications, using single precision is a bad option in my opinion.In some chemistry applications even double precision is not sufficient, where long recursion is involved.
aaa
2010-03-14 19:31:55
+1
A:
Check out the CUDA community showcase: http://www.nvidia.com/object/cuda_showcase_html.html
vasin
2010-03-10 20:06:08