Peter Varhol has a nice piece on GPU vs. CPU computing in Desktop Engineering this week. Not surprisingly, he concludes that you need both when time is on the line:
An ideal configuration is one with one or more CPUs and a set of GPUs that use CUDA or similar parallel computation architecture. All support applications, such as email, web browsing, and word processing use the CPU. And with tools such as Accelereyes Jacket and NVIDIA Nexus, engineering software will eventually take advantage of both to speed up complex computations.
Varhol surmises that the GPU software gap will make it unlikely that engineering teams work strictly on GPUs any time in the foreseeable future. In the meantime, the promise of GPU speed and power efficiency has a lot of folks rolling up their sleeves to port their code.