Without knowing exactly what examples you're running, it may be hard to
say what the problem is. In fact, you may not really have a problem.
How much work is being done in each example program? Is it enough to
really work the GPU, or is communication and other overhead dominating
runtime? Note that laptops may have lower communication latency over
the PCI bus than desktops/servers, which can make small programs run
much faster on laptops regardless of how much processing power the GPU
Have you tried running the sample code from the SDK, so that you can
verify that it's not a code problem?
On Sun, 2012-07-29 at 23:59 -0300, Leandro Demarco Vedelago wrote:
Hello: I've been reading and learning CUDA in the last few weeks
last week I started writing (translating to Pycuda from Cuda-C) some
examples taken from the book "Cuda by Example".
I started coding on a laptop with just one nvidia GPU (a gtx 560M if
my memory is allright) with Windows 7.
But in the project I'm currently working at, we intend to run (py)cuda
on a multi-gpu server that has three Tesla C2075 cards.
So I installed Ubuntu server 10.10 (with no GUI) and managed to
install and get running the very same examples I ran on the single-gpu
laptop. However they run really slow, in some cases it takes 3 times
more than in the laptop. And this happens with most, if not all, the
examples I wrote.
I thought it could be a driver issue but I double-checked and I've
installed the correct ones, meaning those listed on the CUDA Zone
section of nvidia.com
for linux 64-bits. So I'm kind of lost right now
and was wondering if anyone has had this or somewhat similar problem
running on a server.
Sorry for the English, but it's not my native language.
Thanks in advance, Leandro Demarco
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