/* Single-precision 10^x function. Copyright (C) 2020-2024 Free Software Foundation, Inc. This file is part of the GNU C Library. The GNU C Library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. The GNU C Library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with the GNU C Library; if not, see . */ #include #include #include #include #include #include #include #include "math_config.h" /* EXP2F_TABLE_BITS 5 EXP2F_POLY_ORDER 3 Max. ULP error: 0.502 (normal range, nearest rounding). Max. relative error: 2^-33.240 (before rounding to float). Wrong count: 169839. Non-nearest ULP error: 1 (rounded ULP error). Detailed error analysis (for EXP2F_TABLE_BITS=3 thus N=32): - We first compute z = RN(InvLn10N * x) where InvLn10N = N*log(10)/log(2) * (1 + theta1) with |theta1| < 2^-54.150 since z is rounded to nearest: z = InvLn10N * x * (1 + theta2) with |theta2| < 2^-53 thus z = N*log(10)/log(2) * x * (1 + theta3) with |theta3| < 2^-52.463 - Since |x| < 38 in the main branch, we deduce: z = N*log(10)/log(2) * x + theta4 with |theta4| < 2^-40.483 - We then write z = k + r where k is an integer and |r| <= 0.5 (exact) - We thus have x = z*log(2)/(N*log(10)) - theta4*log(2)/(N*log(10)) = z*log(2)/(N*log(10)) + theta5 with |theta5| < 2^-47.215 10^x = 2^(k/N) * 2^(r/N) * 10^theta5 = 2^(k/N) * 2^(r/N) * (1 + theta6) with |theta6| < 2^-46.011 - Then 2^(k/N) is approximated by table lookup, the maximal relative error is for (k%N) = 5, with s = 2^(i/N) * (1 + theta7) with |theta7| < 2^-53.249 - 2^(r/N) is approximated by a degree-3 polynomial, where the maximal mathematical relative error is 2^-33.243. - For C[0] * r + C[1], assuming no FMA is used, since |r| <= 0.5 and |C[0]| < 1.694e-6, |C[0] * r| < 8.47e-7, and the absolute error on C[0] * r is bounded by 1/2*ulp(8.47e-7) = 2^-74. Then we add C[1] with |C[1]| < 0.000235, thus the absolute error on C[0] * r + C[1] is bounded by 2^-65.994 (z is bounded by 0.000236). - For r2 = r * r, since |r| <= 0.5, we have |r2| <= 0.25 and the absolute error is bounded by 1/4*ulp(0.25) = 2^-56 (the factor 1/4 is because |r2| cannot exceed 1/4, and on the left of 1/4 the distance between two consecutive numbers is 1/4*ulp(1/4)). - For y = C[2] * r + 1, assuming no FMA is used, since |r| <= 0.5 and |C[2]| < 0.0217, the absolute error on C[2] * r is bounded by 2^-60, and thus the absolute error on C[2] * r + 1 is bounded by 1/2*ulp(1)+2^60 < 2^-52.988, and |y| < 1.01085 (the error bound is better if a FMA is used). - for z * r2 + y: the absolute error on z is bounded by 2^-65.994, with |z| < 0.000236, and the absolute error on r2 is bounded by 2^-56, with r2 < 0.25, thus |z*r2| < 0.000059, and the absolute error on z * r2 (including the rounding error) is bounded by: 2^-65.994 * 0.25 + 0.000236 * 2^-56 + 1/2*ulp(0.000059) < 2^-66.429. Now we add y, with |y| < 1.01085, and error on y bounded by 2^-52.988, thus the absolute error is bounded by: 2^-66.429 + 2^-52.988 + 1/2*ulp(1.01085) < 2^-51.993 - Now we convert the error on y into relative error. Recall that y approximates 2^(r/N), for |r| <= 0.5 and N=32. Thus 2^(-0.5/32) <= y, and the relative error on y is bounded by 2^-51.993/2^(-0.5/32) < 2^-51.977 - Taking into account the mathematical relative error of 2^-33.243 we have: y = 2^(r/N) * (1 + theta8) with |theta8| < 2^-33.242 - Since we had s = 2^(k/N) * (1 + theta7) with |theta7| < 2^-53.249, after y = y * s we get y = 2^(k/N) * 2^(r/N) * (1 + theta9) with |theta9| < 2^-33.241 - Finally, taking into account the error theta6 due to the rounding error on InvLn10N, and when multiplying InvLn10N * x, we get: y = 10^x * (1 + theta10) with |theta10| < 2^-33.240 - Converting into binary64 ulps, since y < 2^53*ulp(y), the error is at most 2^19.76 ulp(y) - If the result is a binary32 value in the normal range (i.e., >= 2^-126), then the error is at most 2^-9.24 ulps, i.e., less than 0.00166 (in the subnormal range, the error in ulps might be larger). Note that this bound is tight, since for x=-0x25.54ac0p0 the final value of y (before conversion to float) differs from 879853 ulps from the correctly rounded value, and 879853 ~ 2^19.7469. */ #define N (1 << EXP2F_TABLE_BITS) #define InvLn10N (0x3.5269e12f346e2p0 * N) /* log(10)/log(2) to nearest */ #define T __exp2f_data.tab #define C __exp2f_data.poly_scaled #define SHIFT __exp2f_data.shift static inline uint32_t top13 (float x) { return asuint (x) >> 19; } float __exp10f (float x) { uint32_t abstop; uint64_t ki, t; double kd, xd, z, r, r2, y, s; xd = (double) x; abstop = top13 (x) & 0xfff; /* Ignore sign. */ if (__glibc_unlikely (abstop >= top13 (38.0f))) { /* |x| >= 38 or x is nan. */ if (asuint (x) == asuint (-INFINITY)) return 0.0f; if (abstop >= top13 (INFINITY)) return x + x; /* 0x26.8826ap0 is the largest value such that 10^x < 2^128. */ if (x > 0x26.8826ap0f) return __math_oflowf (0); /* -0x2d.278d4p0 is the smallest value such that 10^x > 2^-150. */ if (x < -0x2d.278d4p0f) return __math_uflowf (0); #if WANT_ERRNO_UFLOW if (x < -0x2c.da7cfp0) return __math_may_uflowf (0); #endif /* the smallest value such that 10^x >= 2^-126 (normal range) is x = -0x25.ee060p0 */ /* we go through here for 2014929 values out of 2060451840 (not counting NaN and infinities, i.e., about 0.1% */ } /* x*N*Ln10/Ln2 = k + r with r in [-1/2, 1/2] and int k. */ z = InvLn10N * xd; /* |xd| < 38 thus |z| < 1216 */ #if TOINT_INTRINSICS kd = roundtoint (z); ki = converttoint (z); #else # define SHIFT __exp2f_data.shift kd = math_narrow_eval ((double) (z + SHIFT)); /* Needs to be double. */ ki = asuint64 (kd); kd -= SHIFT; #endif r = z - kd; /* 10^x = 10^(k/N) * 10^(r/N) ~= s * (C0*r^3 + C1*r^2 + C2*r + 1) */ t = T[ki % N]; t += ki << (52 - EXP2F_TABLE_BITS); s = asdouble (t); z = C[0] * r + C[1]; r2 = r * r; y = C[2] * r + 1; y = z * r2 + y; y = y * s; return (float) y; } #ifndef __exp10f strong_alias (__exp10f, __ieee754_exp10f) libm_alias_finite (__ieee754_exp10f, __exp10f) /* For architectures that already provided exp10f without SVID support, there is no need to add a new version. */ #if !LIBM_SVID_COMPAT # define EXP10F_VERSION GLIBC_2_26 #else # define EXP10F_VERSION GLIBC_2_32 #endif versioned_symbol (libm, __exp10f, exp10f, EXP10F_VERSION); libm_alias_float_other (__exp10, exp10) #endif