If you want to learn how to do CUDA programming on a budget, stuffing a GK208 card into a spare computer is great bang-for-the-buck.
However, if you want to benchmark algorithms on a GPU, it is very important to use realistic-sized problems on a realistic-sized GPU. Things will not scale linearly over a large range of problem sizes or GPU sizes. This often leads people to conclude that CUDA is useless because they timed a trivial problem or used a very low-end card.
For that reason, if your budget allows, I would suggest purchasing either a GTX 780 ($650) or a Titan ($1k). If you need double precision or 6 GB of GPU memory, the Titan the better choice, otherwise the GTX 780 is nearly as fast. If you really need to keep the price down, then a GTX 770 is as low as I would go. The GTX 770 is a slightly older architecture (compute capability 3.0), which is why I would tend to avoid it for new purchases.
Aside from that, you want probably 2x as much CPU memory as GPU memory (roughly, depends on exact problem), a PCI-Express 3.0 motherboard and a separate, cheap GPU to run the display.