Special CUDA Double Precision trig functions for SFU

Question

I was wondering how I would go about using __cos(x) (and respectively __sin(x)) in the kernel code with CUDA. I looked up in the CUDA manual that

Answer 1

As the SFU only supports certain single-precision operations, there are no double-precision __cos() and __sin() device functions. There are single-precision __cosf() and __sinf() device functions, as well as other functions detailed in table C-4 of the CUDA 4.2 Programming Manual.

I assume you are looking for faster alternatives to the double-precision versions of the standard math functions sin() and cos()? If sine and cosine of the same argument are needed, sincos() should be used for a significant performance boost. If the argument of sine or cosine is multiplied by π, you would want to use sinpi(), cospi(), or sincospi() instead, for even more performance. For example, sincospi() is very useful when implementing the Box-Muller algorithm for generating normally distributed random numbers. Also, check out the CUDA 5.0 preview for best possible performance (note that the preview provides alpha-release quality).