/* Single-precision 10^x function.
Copyright (C) 2020-2023 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