I have recently discovered the power of GP-GPU (general purpose graphics processing unit) and want to take advantage of it to perform 'heavy' scientific and math calculations (that otherwise require big CPU clusters) on a single machine.

I know that there are several interfaces to operate on a GPU, the most prominent of those being CUDA and OpenCL. The latter has the advantage against CUDA to run on most graphics cards (NVIDIA, AMD, Intel) rather than NVIDA cards only. In my case, I have an ordinary Intel 4000 GPU that seems to be well cooperating with OpenCL.

Now, I need to learn how to operate with PyOpenCL to get it on further! So here comes the question:

**How can I get started with PyOpenCL? What are the prerequisites? Do I really need to be experienced in Python and/or OpenCL?** 

My background is in fortran and as a matter of fact I need to translate and parallelize a lengthy fortran code to python (or pyopencl) that mainly deals with solving PDEs and diagonalizing matrices.

I have read the two relevant websites <http://enja.org/2011/02/22/adventures-in-pyopencl-part-1-getting-started-with-python/> and <http://documen.tician.de/pyopencl/> but they are not really helpful for newbies (ie, dummies). 

I just don't know what to begin with. I do not aspire on becoming an expert on the field, just to get to know how one can parallelize simple math and linear algebra on pyopencl. 

Any advice and help is highly welcome!