Getting Started with GPU Coding: CUDA 5.0

Hello everyone, this is a quick post detailing how to get started with harnessing the potential of your GPU via CUDA. Of course, I am planning to use it for OpenFOAM; I want to translate the pimpleDyMFoam solver for CUDA.

Especially awesome about CUDA 5.0 is the new Nsight IDE for Eclipse. If you have ever programmed with Eclipse (I have in Java), you know how spoiled you can get with all of the real-time automated correction and prediction.

Anyways, here are the steps I took:

I have Ubuntu 12.04, and even though the CUDA toolkit web page has only downloads for Ubuntu 11.10 and 10.04, it really does not matter. I used 11.10 without a hitch.

Download the CUDA toolkit at:
https://developer.nvidia.com/cuda-downloads

Before proceeding make sure you have all required packages:
sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev

Then go to the directory of the download in a terminal. Then type (without the angle brackets):
chmod +x <whatever the name of the download is>
sudo ./<whatever the name of the download is>

If you get an error of some sort like I did, type:
sudo ln -s /usr/lib/x86_64-linux-gnu/libglut.so /usr/lib/libglut.s
And try the 'sudo ...' command again.

The 'sudo ./...' command actually installs three packages: driver, toolkit, and samples. I actually installed the nvidia accelerated graphics driver separately via:

sudo apt-add-repository ppa:ubuntu-x-swat/x-updates
sudo apt-get update
sudo apt-get install nvidia-current

But if the included driver installation works for you, then by all means continue.

Now, add to ~/.bashrc by:
gedit ~/.bashrc
Scroll down to bottom of file and add:
export PATH=/usr/local/cuda-5.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-5.0/lib64:/usr/local/cuda-5.0/lib:$LD_LIBRARY_PATH

Now to test everything out, go to your home directory:
cd ~/
Then go to the cuda samples folder (type 'ls' to view contents).
Once in the samples folder type 'make'. This will compile the sample codes, which may take a while. If you get an error (something like 'cannot find -lcuda', like I did), then type:

sudo ln -s /usr/lib/nvidia-current/libcuda.so /usr/lib/libcuda.so

Then go into the sample files and run the executables (whatever catches your fancy)! Executables are colored green if you view the  file contents via 'ls', and you run the executables by typing './' before the name of the file.