Added batch matrix multiplication, solving triangular system and LU decomposition.

Hi,

First let me thank you for your work making the CUDA libraries usable form python. With these my code will work 100-1000 fold faster and hopefully help me earn my PhD sooner. 

My use case for CUDA is a bit atypical. Most libraries I've seen focus on processing large matrices. What I need to do is run the same program on thousands on small matrices in parallel. Luckily, cublas v5.0 added the routines I need (listed below) so I have added wrappers to those in scikits/cuda/cublas.py.

http://docs.nvidia.com/cuda/cublas/index.html#unique_1756671368
http://docs.nvidia.com/cuda/cublas/index.html#unique_1732840107
http://docs.nvidia.com/cuda/cublas/index.html#topic_8_2

Additionally I wrote tests for these function and a convenience decorator to define the wrappers only if the installed cuda version supports the corresponding library calls. The latter should save some typing. Due to time constraints, I only wrote wrappers for the float32 versions of the functions. 

Hope you'll integrate these changes in the main code-base.

Thanks,
Teodor Moldovan