On Fri, Aug 31, 2007 at 03:48:45PM +0100, Chris Jones wrote: > Does anyone have any recommendations for fast maths ? search around on > the web I've found a lot of references to fast / approximate math > libraries, but nothing obvious. The AMD Core Math library ( http://developer.amd.com/acml.jsp ) is free beer, not F/OSS, but you might want to compare your own results to the documented scalar and vector performance of their transcendental function implementations. [Intel has a more extensive library, but I've never looked through their documentation.] Below are some performance figures excerpted from the ACML v3.6 documentation. In addition to the scalar and general vector versions, there are also specialized versions for 2-vectors and 4-vectors. The documentation for each of these functions says: "the routine is accurate to better than 1 ulp over the valid input range." [ulp = unit in the last place, i.e., the trailing bit.] fastexp: fast double precision exponential function : double fastexp (double x) * Performance: + 75 cycles for most valid inputs. vrda_exp: Array double precision exponential function : void vrda_exp (int n, double *x, double *y) * Performance: + 33 cycles per value for valid inputs, n = 24. fastlog: fast double precision natural logarithm function : double fastlog (double x) * Performance: + 97 cycles for most valid inputs. 86 cycles for .97 < x < 1.03 vrda_log: Array double precision natural logarithm : void vrda_log (int n, double *x, double *y) * Performance: + 51 cycles per value for valid inputs, n = 24. Regards, Bill Rugolsky
