Single precision is about 2.5x faster than double precision on current GPUs (for matrix multiplication, which is compute dominated). It really depends on the application, but in my experience more often than not the only reason you are using GPUs is because you want to squeeze out every last ounce of performance. In these cases, single precision makes a lot of sense (assuming you're algorithm doesn't depend heavily on 64 bits of precision).

Within the neural nets community, single precision is almost always used (at least on GPUs).