CUDA is one of Nvidia’s greatest gifts for the everyday programmer who dreams of a parallelised world. With most computer/laptops now taking aboard at least one dedicated graphics processor, the prospect of parallel tools for all is becoming a reality. Soon enough everyone no matter what your sex, will be able to multi-task.
I write this as I recently had to upgrade my laptop. I wanted to reinstate my GeForce 640M Nvidia graphics card installing with the latest drivers (331.49) and software for CUDA (v5.5). This turns out is not so trivial as CUDA-5.5 will not run with the latest gcc compilers (gcc4.6+) at present, so you can’t use C++11 :(… However, I came across the two following posts which provided some novel solutions to this problem and now everything works great! I hope they may help someone else out there. Read these both first, just so you are aware of what need be done. The first is merely the process to install the drivers, the second provides more detail into what you should do to make it work on the latest gcc versions although it is a bit of a hack but does the job. Read them both!
You can check the install was ok by running a simple example and/or typing the following command.
I will get around to posting more about CUDA in particular, the use of Thrust which is a STL like interface enabling you to devise neat and familiar C++ looking parallel code for a large chunk of parallel applications . It is seriously cool!
For a neat intro to parallel programming see these talks, they know their stuff:-