/* * Adapted from OpenImageIO library with this license: * * Copyright 2008-2014 Larry Gritz and the other authors and contributors. * All Rights Reserved. * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of the software's owners nor the names of its * contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * * (This is the Modified BSD License) * * A few bits here are based upon code from NVIDIA that was also released * under the same modified BSD license, and marked as: * Copyright 2004 NVIDIA Corporation. All Rights Reserved. * * Some parts of this file were first open-sourced in Open Shading Language, * then later moved here. The original copyright notice was: * Copyright (c) 2009-2014 Sony Pictures Imageworks Inc., et al. * * Many of the math functions were copied from or inspired by other * public domain sources or open source packages with compatible licenses. * The individual functions give references were applicable. */ #ifndef __UTIL_FAST_MATH__ #define __UTIL_FAST_MATH__ CCL_NAMESPACE_BEGIN ccl_device_inline float madd(const float a, const float b, const float c) { /* NOTE: In the future we may want to explicitly ask for a fused * multiply-add in a specialized version for float. * * NOTE: GCC/ICC will turn this (for float) into a FMA unless * explicitly asked not to, clang seems to leave the code alone. */ return a * b + c; } ccl_device_inline float4 madd4(const float4 a, const float4 b, const float4 c) { return a * b + c; } /* * FAST & APPROXIMATE MATH * * The functions named "fast_*" provide a set of replacements to libm that * are much faster at the expense of some accuracy and robust handling of * extreme values. One design goal for these approximation was to avoid * branches as much as possible and operate on single precision values only * so that SIMD versions should be straightforward ports We also try to * implement "safe" semantics (ie: clamp to valid range where possible) * natively since wrapping these inline calls in another layer would be * wasteful. * * Some functions are fast_safe_*, which is both a faster approximation as * well as clamped input domain to ensure no NaN, Inf, or divide by zero. */ /* Round to nearest integer, returning as an int. */ ccl_device_inline int fast_rint(float x) { /* used by sin/cos/tan range reduction. */ #ifdef __KERNEL_SSE4__ /* Single roundps instruction on SSE4.1+ (for gcc/clang at least). */ return float_to_int(rintf(x)); #else /* emulate rounding by adding/substracting 0.5. */ return float_to_int(x + copysignf(0.5f, x)); #endif } ccl_device float fast_sinf(float x) { /* Very accurate argument reduction from SLEEF, * starts failing around x=262000 * * Results on: [-2pi,2pi]. * * Examined 2173837240 values of sin: 0.00662760244 avg ulp diff, 2 max ulp, * 1.19209e-07 max error */ int q = fast_rint(x * M_1_PI_F); float qf = q; x = madd(qf, -0.78515625f*4, x); x = madd(qf, -0.00024187564849853515625f*4, x); x = madd(qf, -3.7747668102383613586e-08f*4, x); x = madd(qf, -1.2816720341285448015e-12f*4, x); x = M_PI_2_F - (M_PI_2_F - x); /* Crush denormals */ float s = x * x; if((q & 1) != 0) x = -x; /* This polynomial approximation has very low error on [-pi/2,+pi/2] * 1.19209e-07 max error in total over [-2pi,+2pi]. */ float u = 2.6083159809786593541503e-06f; u = madd(u, s, -0.0001981069071916863322258f); u = madd(u, s, +0.00833307858556509017944336f); u = madd(u, s, -0.166666597127914428710938f); u = madd(s, u * x, x); /* For large x, the argument reduction can fail and the polynomial can be * evaluated with arguments outside the valid internal. Just clamp the bad * values away (setting to 0.0f means no branches need to be generated). */ if(fabsf(u) > 1.0f) { u = 0.0f; } return u; } ccl_device float fast_cosf(float x) { /* Same argument reduction as fast_sinf(). */ int q = fast_rint(x * M_1_PI_F); float qf = q; x = madd(qf, -0.78515625f*4, x); x = madd(qf, -0.00024187564849853515625f*4, x); x = madd(qf, -3.7747668102383613586e-08f*4, x); x = madd(qf, -1.2816720341285448015e-12f*4, x); x = M_PI_2_F - (M_PI_2_F - x); /* Crush denormals. */ float s = x * x; /* Polynomial from SLEEF's sincosf, max error is * 4.33127e-07 over [-2pi,2pi] (98% of values are "exact"). */ float u = -2.71811842367242206819355e-07f; u = madd(u, s, +2.47990446951007470488548e-05f); u = madd(u, s, -0.00138888787478208541870117f); u = madd(u, s, +0.0416666641831398010253906f); u = madd(u, s, -0.5f); u = madd(u, s, +1.0f); if((q & 1) != 0) { u = -u; } if(fabsf(u) > 1.0f) { u = 0.0f; } return u; } ccl_device void fast_sincosf(float x, float* sine, float* cosine) { /* Same argument reduction as fast_sin. */ int q = fast_rint(x * M_1_PI_F); float qf = q; x = madd(qf, -0.78515625f*4, x); x = madd(qf, -0.00024187564849853515625f*4, x); x = madd(qf, -3.7747668102383613586e-08f*4, x); x = madd(qf, -1.2816720341285448015e-12f*4, x); x = M_PI_2_F - (M_PI_2_F - x); // crush denormals float s = x * x; /* NOTE: same exact polynomials as fast_sinf() and fast_cosf() above. */ if((q & 1) != 0) { x = -x; } float su = 2.6083159809786593541503e-06f; su = madd(su, s, -0.0001981069071916863322258f); su = madd(su, s, +0.00833307858556509017944336f); su = madd(su, s, -0.166666597127914428710938f); su = madd(s, su * x, x); float cu = -2.71811842367242206819355e-07f; cu = madd(cu, s, +2.47990446951007470488548e-05f); cu = madd(cu, s, -0.00138888787478208541870117f); cu = madd(cu, s, +0.0416666641831398010253906f); cu = madd(cu, s, -0.5f); cu = madd(cu, s, +1.0f); if((q & 1) != 0) { cu = -cu; } if(fabsf(su) > 1.0f) { su = 0.0f; } if(fabsf(cu) > 1.0f) { cu = 0.0f; } *sine = su; *cosine = cu; } /* NOTE: this approximation is only valid on [-8192.0,+8192.0], it starts * becoming really poor outside of this range because the reciprocal amplifies * errors. */ ccl_device float fast_tanf(float x) { /* Derived from SLEEF implementation. * * Note that we cannot apply the "denormal crush" trick everywhere because * we sometimes need to take the reciprocal of the polynomial */ int q = fast_rint(x * 2.0f * M_1_PI_F); float qf = q; x = madd(qf, -0.78515625f*2, x); x = madd(qf, -0.00024187564849853515625f*2, x); x = madd(qf, -3.7747668102383613586e-08f*2, x); x = madd(qf, -1.2816720341285448015e-12f*2, x); if((q & 1) == 0) { /* Crush denormals (only if we aren't inverting the result later). */ x = M_PI_4_F - (M_PI_4_F - x); } float s = x * x; float u = 0.00927245803177356719970703f; u = madd(u, s, 0.00331984995864331722259521f); u = madd(u, s, 0.0242998078465461730957031f); u = madd(u, s, 0.0534495301544666290283203f); u = madd(u, s, 0.133383005857467651367188f); u = madd(u, s, 0.333331853151321411132812f); u = madd(s, u * x, x); if((q & 1) != 0) { u = -1.0f / u; } return u; } /* Fast, approximate sin(x*M_PI) with maximum absolute error of 0.000918954611. * * Adapted from http://devmaster.net/posts/9648/fast-and-accurate-sine-cosine#comment-76773 */ ccl_device float fast_sinpif(float x) { /* Fast trick to strip the integral part off, so our domain is [-1, 1]. */ const float z = x - ((x + 25165824.0f) - 25165824.0f); const float y = z - z * fabsf(z); const float Q = 3.10396624f; const float P = 3.584135056f; /* P = 16-4*Q */ return y * (Q + P * fabsf(y)); /* The original article used used inferior constants for Q and P and * so had max error 1.091e-3. * * The optimal value for Q was determined by exhaustive search, minimizing * the absolute numerical error relative to float(std::sin(double(phi*M_PI))) * over the interval [0,2] (which is where most of the invocations happen). * * The basic idea of this approximation starts with the coarse approximation: * sin(pi*x) ~= f(x) = 4 * (x - x * abs(x)) * * This approximation always _over_ estimates the target. On the other hand, * the curve: * sin(pi*x) ~= f(x) * abs(f(x)) / 4 * * always lies _under_ the target. Thus we can simply numerically search for * the optimal constant to LERP these curves into a more precise * approximation. * * After folding the constants together and simplifying the resulting math, * we end up with the compact implementation above. * * NOTE: this function actually computes sin(x * pi) which avoids one or two * mults in many cases and guarantees exact values at integer periods. */ } /* Fast approximate cos(x*M_PI) with ~0.1% absolute error. */ ccl_device_inline float fast_cospif(float x) { return fast_sinpif(x+0.5f); } ccl_device float fast_acosf(float x) { const float f = fabsf(x); /* clamp and crush denormals. */ const float m = (f < 1.0f) ? 1.0f - (1.0f - f) : 1.0f; /* Based on http://www.pouet.net/topic.php?which=9132&page=2 * 85% accurate (ulp 0) * Examined 2130706434 values of acos: 15.2000597 avg ulp diff, 4492 max ulp, 4.51803e-05 max error // without "denormal crush" * Examined 2130706434 values of acos: 15.2007108 avg ulp diff, 4492 max ulp, 4.51803e-05 max error // with "denormal crush" */ const float a = sqrtf(1.0f - m) * (1.5707963267f + m * (-0.213300989f + m * (0.077980478f + m * -0.02164095f))); return x < 0 ? M_PI_F - a : a; } ccl_device float fast_asinf(float x) { /* Based on acosf approximation above. * Max error is 4.51133e-05 (ulps are higher because we are consistently off * by a little amount). */ const float f = fabsf(x); /* Clamp and crush denormals. */ const float m = (f < 1.0f) ? 1.0f - (1.0f - f) : 1.0f; const float a = M_PI_2_F - sqrtf(1.0f - m) * (1.5707963267f + m * (-0.213300989f + m * (0.077980478f + m * -0.02164095f))); return copysignf(a, x); } ccl_device float fast_atanf(float x) { const float a = fabsf(x); const float k = a > 1.0f ? 1 / a : a; const float s = 1.0f - (1.0f - k); /* Crush denormals. */ const float t = s * s; /* http://mathforum.org/library/drmath/view/62672.html * Examined 4278190080 values of atan: 2.36864877 avg ulp diff, 302 max ulp, 6.55651e-06 max error // (with denormals) * Examined 4278190080 values of atan: 171160502 avg ulp diff, 855638016 max ulp, 6.55651e-06 max error // (crush denormals) */ float r = s * madd(0.43157974f, t, 1.0f) / madd(madd(0.05831938f, t, 0.76443945f), t, 1.0f); if(a > 1.0f) { r = M_PI_2_F - r; } return copysignf(r, x); } ccl_device float fast_atan2f(float y, float x) { /* Based on atan approximation above. * * The special cases around 0 and infinity were tested explicitly. * * The only case not handled correctly is x=NaN,y=0 which returns 0 instead * of nan. */ const float a = fabsf(x); const float b = fabsf(y); const float k = (b == 0) ? 0.0f : ((a == b) ? 1.0f : (b > a ? a / b : b / a)); const float s = 1.0f - (1.0f - k); /* Crush denormals */ const float t = s * s; float r = s * madd(0.43157974f, t, 1.0f) / madd(madd(0.05831938f, t, 0.76443945f), t, 1.0f); if(b > a) { /* Account for arg reduction. */ r = M_PI_2_F - r; } /* Test sign bit of x. */ if(__float_as_uint(x) & 0x80000000u) { r = M_PI_F - r; } return copysignf(r, y); } /* Based on: * * https://github.com/LiraNuna/glsl-sse2/blob/master/source/vec4.h * */ ccl_device float fast_log2f(float x) { /* NOTE: clamp to avoid special cases and make result "safe" from large * negative values/nans. */ x = clamp(x, FLT_MIN, FLT_MAX); unsigned bits = __float_as_uint(x); int exponent = (int)(bits >> 23) - 127; float f = __uint_as_float((bits & 0x007FFFFF) | 0x3f800000) - 1.0f; /* Examined 2130706432 values of log2 on [1.17549435e-38,3.40282347e+38]: * 0.0797524457 avg ulp diff, 3713596 max ulp, 7.62939e-06 max error. * ulp histogram: * 0 = 97.46% * 1 = 2.29% * 2 = 0.11% */ float f2 = f * f; float f4 = f2 * f2; float hi = madd(f, -0.00931049621349f, 0.05206469089414f); float lo = madd(f, 0.47868480909345f, -0.72116591947498f); hi = madd(f, hi, -0.13753123777116f); hi = madd(f, hi, 0.24187369696082f); hi = madd(f, hi, -0.34730547155299f); lo = madd(f, lo, 1.442689881667200f); return ((f4 * hi) + (f * lo)) + exponent; } ccl_device_inline float fast_logf(float x) { /* Examined 2130706432 values of logf on [1.17549435e-38,3.40282347e+38]: * 0.313865375 avg ulp diff, 5148137 max ulp, 7.62939e-06 max error. */ return fast_log2f(x) * M_LN2_F; } ccl_device_inline float fast_log10(float x) { /* Examined 2130706432 values of log10f on [1.17549435e-38,3.40282347e+38]: * 0.631237033 avg ulp diff, 4471615 max ulp, 3.8147e-06 max error. */ return fast_log2f(x) * M_LN2_F / M_LN10_F; } ccl_device float fast_logb(float x) { /* Don't bother with denormals. */ x = fabsf(x); x = clamp(x, FLT_MIN, FLT_MAX); unsigned bits = __float_as_uint(x); return (int)(bits >> 23) - 127; } ccl_device float fast_exp2f(float x) { /* Clamp to safe range for final addition. */ x = clamp(x, -126.0f, 126.0f); /* Range reduction. */ int m = (int)x; x -= m; x = 1.0f - (1.0f - x); /* Crush denormals (does not affect max ulps!). */ /* 5th degree polynomial generated with sollya * Examined 2247622658 values of exp2 on [-126,126]: 2.75764912 avg ulp diff, * 232 max ulp. * * ulp histogram: * 0 = 87.81% * 1 = 4.18% */ float r = 1.33336498402e-3f; r = madd(x, r, 9.810352697968e-3f); r = madd(x, r, 5.551834031939e-2f); r = madd(x, r, 0.2401793301105f); r = madd(x, r, 0.693144857883f); r = madd(x, r, 1.0f); /* Multiply by 2 ^ m by adding in the exponent. */ /* NOTE: left-shift of negative number is undefined behavior. */ return __uint_as_float(__float_as_uint(r) + ((unsigned)m << 23)); } ccl_device_inline float fast_expf(float x) { /* Examined 2237485550 values of exp on [-87.3300018,87.3300018]: * 2.6666452 avg ulp diff, 230 max ulp. */ return fast_exp2f(x / M_LN2_F); } #ifndef __KERNEL_GPU__ ccl_device float4 fast_exp2f4(float4 x) { const float4 one = make_float4(1.0f); const float4 limit = make_float4(126.0f); x = clamp(x, -limit, limit); int4 m = make_int4(x); x = one - (one - (x - make_float4(m))); float4 r = make_float4(1.33336498402e-3f); r = madd4(x, r, make_float4(9.810352697968e-3f)); r = madd4(x, r, make_float4(5.551834031939e-2f)); r = madd4(x, r, make_float4(0.2401793301105f)); r = madd4(x, r, make_float4(0.693144857883f)); r = madd4(x, r, make_float4(1.0f)); return __int4_as_float4(__float4_as_int4(r) + (m << 23)); } ccl_device_inline float4 fast_expf4(float4 x) { return fast_exp2f4(x / M_LN2_F); } #endif ccl_device_inline float fast_exp10(float x) { /* Examined 2217701018 values of exp10 on [-37.9290009,37.9290009]: * 2.71732409 avg ulp diff, 232 max ulp. */ return fast_exp2f(x * M_LN10_F / M_LN2_F); } ccl_device_inline float fast_expm1f(float x) { if(fabsf(x) < 1e-5f) { x = 1.0f - (1.0f - x); /* Crush denormals. */ return madd(0.5f, x * x, x); } else { return fast_expf(x) - 1.0f; } } ccl_device float fast_sinhf(float x) { float a = fabsf(x); if(a > 1.0f) { /* Examined 53389559 values of sinh on [1,87.3300018]: * 33.6886442 avg ulp diff, 178 max ulp. */ float e = fast_expf(a); return copysignf(0.5f * e - 0.5f / e, x); } else { a = 1.0f - (1.0f - a); /* Crush denorms. */ float a2 = a * a; /* Degree 7 polynomial generated with sollya. */ /* Examined 2130706434 values of sinh on [-1,1]: 1.19209e-07 max error. */ float r = 2.03945513931e-4f; r = madd(r, a2, 8.32990277558e-3f); r = madd(r, a2, 0.1666673421859f); r = madd(r * a, a2, a); return copysignf(r, x); } } ccl_device_inline float fast_coshf(float x) { /* Examined 2237485550 values of cosh on [-87.3300018,87.3300018]: * 1.78256726 avg ulp diff, 178 max ulp. */ float e = fast_expf(fabsf(x)); return 0.5f * e + 0.5f / e; } ccl_device_inline float fast_tanhf(float x) { /* Examined 4278190080 values of tanh on [-3.40282347e+38,3.40282347e+38]: * 3.12924e-06 max error. */ /* NOTE: ulp error is high because of sub-optimal handling around the origin. */ float e = fast_expf(2.0f * fabsf(x)); return copysignf(1.0f - 2.0f / (1.0f + e), x); } ccl_device float fast_safe_powf(float x, float y) { if(y == 0) return 1.0f; /* x^1=1 */ if(x == 0) return 0.0f; /* 0^y=0 */ float sign = 1.0f; if(x < 0.0f) { /* if x is negative, only deal with integer powers * powf returns NaN for non-integers, we will return 0 instead. */ int ybits = __float_as_int(y) & 0x7fffffff; if(ybits >= 0x4b800000) { // always even int, keep positive } else if(ybits >= 0x3f800000) { /* Bigger than 1, check. */ int k = (ybits >> 23) - 127; /* Get exponent. */ int j = ybits >> (23 - k); /* Shift out possible fractional bits. */ if((j << (23 - k)) == ybits) { /* rebuild number and check for a match. */ /* +1 for even, -1 for odd. */ sign = __int_as_float(0x3f800000 | (j << 31)); } else { /* Not an integer. */ return 0.0f; } } else { /* Not an integer. */ return 0.0f; } } return sign * fast_exp2f(y * fast_log2f(fabsf(x))); } /* TODO(sergey): Check speed with our erf functions implementation from * bsdf_microfacet.h. */ ccl_device_inline float fast_erff(float x) { /* Examined 1082130433 values of erff on [0,4]: 1.93715e-06 max error. */ /* Abramowitz and Stegun, 7.1.28. */ const float a1 = 0.0705230784f; const float a2 = 0.0422820123f; const float a3 = 0.0092705272f; const float a4 = 0.0001520143f; const float a5 = 0.0002765672f; const float a6 = 0.0000430638f; const float a = fabsf(x); if(a >= 12.3f) { return copysignf(1.0f, x); } const float b = 1.0f - (1.0f - a); /* Crush denormals. */ const float r = madd(madd(madd(madd(madd(madd(a6, b, a5), b, a4), b, a3), b, a2), b, a1), b, 1.0f); const float s = r * r; /* ^2 */ const float t = s * s; /* ^4 */ const float u = t * t; /* ^8 */ const float v = u * u; /* ^16 */ return copysignf(1.0f - 1.0f / v, x); } ccl_device_inline float fast_erfcf(float x) { /* Examined 2164260866 values of erfcf on [-4,4]: 1.90735e-06 max error. * * ulp histogram: * * 0 = 80.30% */ return 1.0f - fast_erff(x); } ccl_device_inline float fast_ierff(float x) { /* From: Approximating the erfinv function by Mike Giles. */ /* To avoid trouble at the limit, clamp input to 1-eps. */ float a = fabsf(x); if(a > 0.99999994f) { a = 0.99999994f; } float w = -fast_logf((1.0f - a) * (1.0f + a)), p; if(w < 5.0f) { w = w - 2.5f; p = 2.81022636e-08f; p = madd(p, w, 3.43273939e-07f); p = madd(p, w, -3.5233877e-06f); p = madd(p, w, -4.39150654e-06f); p = madd(p, w, 0.00021858087f); p = madd(p, w, -0.00125372503f); p = madd(p, w, -0.00417768164f); p = madd(p, w, 0.246640727f); p = madd(p, w, 1.50140941f); } else { w = sqrtf(w) - 3.0f; p = -0.000200214257f; p = madd(p, w, 0.000100950558f); p = madd(p, w, 0.00134934322f); p = madd(p, w, -0.00367342844f); p = madd(p, w, 0.00573950773f); p = madd(p, w, -0.0076224613f); p = madd(p, w, 0.00943887047f); p = madd(p, w, 1.00167406f); p = madd(p, w, 2.83297682f); } return p * x; } CCL_NAMESPACE_END #endif /* __UTIL_FAST_MATH__ */