Backport fmath performance and other fixes from OSL #2495
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Any objections to any of this? |
A variety of minor rewrites of certain math functions to ensure they generate better machine code and auto-vectorize more cleanly. * Lots of inline -> OIIO_FORCEINLINE * Improve clamp used in fast_sin and cos * fast_safe_pow improve code gen with OIIO_UNLIKELY * Introduce `OIIO_FMATH_SIMD_FRIENDLY` to allow application switching between implementations that give the best scalar performance versus sacrificing scalar perf to have the best SIMD vectorization of loops containing the fmath function. This is anticipated to be very rare, and of course we strive to be simultaneously fastest on scalar & simd, but we have one or two cases where such a tradeoff exists. * Lots of additional fmath benchmarks to help us judge how good they are compared to std functions. * New safe_fmod which not only prevents division by zero but even in other cases is much faster than std::fmod. * New fast_neg is faster than `-float`, in cases where you are ok with -(0.0f) being 0.0f instead of actual floating point -0.0f. If you have no idea what I'm talking about or why it matters, you definitely will like this function! * Most of these improvements were backported from OSL, made by Alex Wells, Intel.
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Merging. If anything turns up to be an issue later, we can always amend. |
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…oundation#2495) A variety of minor rewrites of certain math functions to ensure they generate better machine code and auto-vectorize more cleanly. * Lots of inline -> OIIO_FORCEINLINE * Improve clamp used in fast_sin and cos * fast_safe_pow improve code gen with OIIO_UNLIKELY * Introduce `OIIO_FMATH_SIMD_FRIENDLY` to allow application switching between implementations that give the best scalar performance versus sacrificing scalar perf to have the best SIMD vectorization of loops containing the fmath function. This is anticipated to be very rare, and of course we strive to be simultaneously fastest on scalar & simd, but we have one or two cases where such a tradeoff exists. * Lots of additional fmath benchmarks to help us judge how good they are compared to std functions. * New safe_fmod which not only prevents division by zero but even in other cases is much faster than std::fmod. * New fast_neg is faster than `-float`, in cases where you are ok with -(0.0f) being 0.0f instead of actual floating point -0.0f. If you have no idea what I'm talking about or why it matters, you definitely will like this function! * Most of these improvements were backported from OSL, made by Alex Wells, Intel.
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A variety of minor rewrites of certain math functions to ensure they
generate better machine code and auto-vectorize more cleanly.
Lots of inline -> OIIO_FORCEINLINE
Improve clamp used in fast_sin and cos
fast_safe_pow improve code gen with OIIO_UNLIKELY
Introduce
OIIO_FMATH_SIMD_FRIENDLYto allow application switchingbetween implementations that give the best scalar performance versus
sacrificing scalar perf to have the best SIMD vectorization of loops
containing the fmath function. This is anticipated to be very rare,
and of course we strive to be simultaneously fastest on scalar & simd,
but we have one or two cases where such a tradeoff exists.
Lots of additional fmath benchmarks to help us judge how good they are
compared to std functions.
New safe_fmod which not only prevents division by zero but even in other
cases is much faster than std::fmod.
New fast_neg is faster than
-float, in cases where you are ok with-(0.0f) being 0.0f instead of actual floating point -0.0f. If you have
no idea what I'm talking about or why it matters, you definitely will
like this function!
Most of these improvements were backported from OSL, made by Alex Wells,
Intel.