<p>I'm currently implementing a raytracer. Since raytracing is extremely computation heavy and since I am going to be looking into CUDA programming anyway, I was wondering if anyone has any experience with combining the two. I can't really tell if the computational models match and I would like to know what to expect. I get the impression that it's not exactly a match made in heaven, but a decent speed increasy would be better than nothing.</p>

It can certainly be done, has been done, and is a hot topic currently among the raytracing and Cuda gurus.  I'd start by perusing
http://www.nvidia.com/object/cuda_home.html
But it's basically a research problem.  People who are doing it well are getting peer-reviewed research papers out of it.  But
well
at this point still means that the best GPU/Cuda results are approximately competitive with best-of-class solutions on CPU/multi-core/SSE.  So I think that it's a little early to assume that using Cuda is going to accelerate a ray tracer.  The problem is that although ray tracing is "embarrassingly parallel" (as they say), it is not the kind of "fixed input and output size" problem that maps straightforwardly to GPUs -- you want trees, stacks, dynamic data structures, etc.  It can be done with Cuda/GPU, but it's tricky.
Your question wasn't clear about your experience level or the goals of your project.  If this is your first ray tracer and you're just trying to learn, I'd avoid Cuda -- it'll take you 10x longer to develop and you probably won't get good speed.  If you're a moderately experienced Cuda programmer and are looking for a challenging project and ray tracing is just a fun thing to learn, by all means, try to do it in Cuda.  If you're making a commercial app and you're looking to get a competitive speed edge -- well, it's probably a crap shoot at this point... you might get a performance edge, but at the expense of more difficult development and dependence on particular hardware.
Check back in a year, the answer may be different after another generation or two of GPU speed, Cuda compiler development, and research community experience.