Things are moving rapidly in the Graphics Processing Unit (GPU) programming arena. NVIDIA just released CUDA a GPU compiler that will allow applications to offload work to the GPU. Most GPUs run about 10 times faster than their host CPU and are ideal for running uniform mathematical operations on large sets of data.
NVIDIA is adding a nice compiler that does the hard work of translating your math into GPU assembly code. All you have to do is provide the source code of the program, compile it and upload the program and data to the graphics processor and get the results. ATI is apparently going with a much more barebones approach and allowing you to program the GPU in assembly code directly. That is more flexible, but requires someone else to develop and support the toolset. I like NVIDIA's solution better, but I don't think that they allow you direct access to assembly so it is a little less flexible.
GPU programming is going to become a big deal in scientific computing in the next few years.