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//===-- Implementation of cbrt function -----------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
#include "src/math/cbrt.h"
#include "hdr/fenv_macros.h"
#include "src/__support/FPUtil/FEnvImpl.h"
#include "src/__support/FPUtil/FPBits.h"
#include "src/__support/FPUtil/PolyEval.h"
#include "src/__support/FPUtil/double_double.h"
#include "src/__support/FPUtil/dyadic_float.h"
#include "src/__support/FPUtil/multiply_add.h"
#include "src/__support/common.h"
#include "src/__support/integer_literals.h"
#include "src/__support/macros/config.h"
#include "src/__support/macros/optimization.h" // LIBC_UNLIKELY
#if ((LIBC_MATH & LIBC_MATH_SKIP_ACCURATE_PASS) != 0)
#define LIBC_MATH_CBRT_SKIP_ACCURATE_PASS
#endif
namespace LIBC_NAMESPACE_DECL {
using DoubleDouble = fputil::DoubleDouble;
using Float128 = fputil::DyadicFloat<128>;
namespace {
// Initial approximation of x^(-2/3) for 1 <= x < 2.
// Polynomial generated by Sollya with:
// > P = fpminimax(x^(-2/3), 7, [|D...|], [1, 2]);
// > dirtyinfnorm(P/x^(-2/3) - 1, [1, 2]);
// 0x1.28...p-21
double intial_approximation(double x) {
constexpr double COEFFS[8] = {
0x1.bc52aedead5c6p1, -0x1.b52bfebf110b3p2, 0x1.1d8d71d53d126p3,
-0x1.de2db9e81cf87p2, 0x1.0154ca06153bdp2, -0x1.5973c66ee6da7p0,
0x1.07bf6ac832552p-2, -0x1.5e53d9ce41cb8p-6,
};
double x_sq = x * x;
double c0 = fputil::multiply_add(x, COEFFS[1], COEFFS[0]);
double c1 = fputil::multiply_add(x, COEFFS[3], COEFFS[2]);
double c2 = fputil::multiply_add(x, COEFFS[5], COEFFS[4]);
double c3 = fputil::multiply_add(x, COEFFS[7], COEFFS[6]);
double x_4 = x_sq * x_sq;
double d0 = fputil::multiply_add(x_sq, c1, c0);
double d1 = fputil::multiply_add(x_sq, c3, c2);
return fputil::multiply_add(x_4, d1, d0);
}
// Get the error term for Newton iteration:
// h(x) = x^3 * a^2 - 1,
#ifdef LIBC_TARGET_CPU_HAS_FMA
double get_error(const DoubleDouble &x_3, const DoubleDouble &a_sq) {
return fputil::multiply_add(x_3.hi, a_sq.hi, -1.0) +
fputil::multiply_add(x_3.lo, a_sq.hi, x_3.hi * a_sq.lo);
}
#else
double get_error(const DoubleDouble &x_3, const DoubleDouble &a_sq) {
DoubleDouble x_3_a_sq = fputil::quick_mult(a_sq, x_3);
return (x_3_a_sq.hi - 1.0) + x_3_a_sq.lo;
}
#endif
} // anonymous namespace
// Correctly rounded cbrt algorithm:
//
// === Step 1 - Range reduction ===
// For x = (-1)^s * 2^e * (1.m), we get 2 reduced arguments x_r and a as:
// x_r = 1.m
// a = (-1)^s * 2^(e % 3) * (1.m)
// Then cbrt(x) = x^(1/3) can be computed as:
// x^(1/3) = 2^(e / 3) * a^(1/3).
//
// In order to avoid division, we compute a^(-2/3) using Newton method and then
// multiply the results by a:
// a^(1/3) = a * a^(-2/3).
//
// === Step 2 - First approximation to a^(-2/3) ===
// First, we use a degree-7 minimax polynomial generated by Sollya to
// approximate x_r^(-2/3) for 1 <= x_r < 2.
// p = P(x_r) ~ x_r^(-2/3),
// with relative errors bounded by:
// | p / x_r^(-2/3) - 1 | < 1.16 * 2^-21.
//
// Then we multiply with 2^(e % 3) from a small lookup table to get:
// x_0 = 2^(-2*(e % 3)/3) * p
// ~ 2^(-2*(e % 3)/3) * x_r^(-2/3)
// = a^(-2/3)
// With relative errors:
// | x_0 / a^(-2/3) - 1 | < 1.16 * 2^-21.
// This step is done in double precision.
//
// === Step 3 - First Newton iteration ===
// We follow the method described in:
// Sibidanov, A. and Zimmermann, P., "Correctly rounded cubic root evaluation
// in double precision", https://core-math.gitlabpages.inria.fr/cbrt64.pdf
// to derive multiplicative Newton iterations as below:
// Let x_n be the nth approximation to a^(-2/3). Define the n^th error as:
// h_n = x_n^3 * a^2 - 1
// Then:
// a^(-2/3) = x_n / (1 + h_n)^(1/3)
// = x_n * (1 - (1/3) * h_n + (2/9) * h_n^2 - (14/81) * h_n^3 + ...)
// using the Taylor series expansion of (1 + h_n)^(-1/3).
//
// Apply to x_0 above:
// h_0 = x_0^3 * a^2 - 1
// = a^2 * (x_0 - a^(-2/3)) * (x_0^2 + x_0 * a^(-2/3) + a^(-4/3)),
// it's bounded by:
// |h_0| < 4 * 3 * 1.16 * 2^-21 * 4 < 2^-17.
// So in the first iteration step, we use:
// x_1 = x_0 * (1 - (1/3) * h_n + (2/9) * h_n^2 - (14/81) * h_n^3)
// Its relative error is bounded by:
// | x_1 / a^(-2/3) - 1 | < 35/242 * |h_0|^4 < 2^-70.
// Then we perform Ziv's rounding test and check if the answer is exact.
// This step is done in double-double precision.
//
// === Step 4 - Second Newton iteration ===
// If the Ziv's rounding test from the previous step fails, we define the error
// term:
// h_1 = x_1^3 * a^2 - 1,
// And perform another iteration:
// x_2 = x_1 * (1 - h_1 / 3)
// with the relative errors exceed the precision of double-double.
// We then check the Ziv's accuracy test with relative errors < 2^-102 to
// compensate for rounding errors.
//
// === Step 5 - Final iteration ===
// If the Ziv's accuracy test from the previous step fails, we perform another
// iteration in 128-bit precision and check for exact outputs.
//
// TODO: It is possible to replace this costly computation step with special
// exceptional handling, similar to what was done in the CORE-MATH project:
// https://gitlab.inria.fr/core-math/core-math/-/blob/master/src/binary64/cbrt/cbrt.c
LLVM_LIBC_FUNCTION(double, cbrt, (double x)) {
using FPBits = fputil::FPBits<double>;
uint64_t x_abs = FPBits(x).abs().uintval();
unsigned exp_bias_correction = 682; // 1023 * 2/3
if (LIBC_UNLIKELY(x_abs < FPBits::min_normal().uintval() ||
x_abs >= FPBits::inf().uintval())) {
if (x_abs == 0 || x_abs >= FPBits::inf().uintval())
// x is 0, Inf, or NaN.
return x;
// x is non-zero denormal number.
// Normalize x.
x *= 0x1.0p60;
exp_bias_correction -= 20;
}
FPBits x_bits(x);
// When using biased exponent of x in double precision,
// x_e = real_exponent_of_x + 1023
// Then:
// x_e / 3 = real_exponent_of_x / 3 + 1023/3
// = real_exponent_of_x / 3 + 341
// So to make it the correct biased exponent of x^(1/3), we add
// 1023 - 341 = 682
// to the quotient x_e / 3.
unsigned x_e = static_cast<unsigned>(x_bits.get_biased_exponent());
unsigned out_e = (x_e / 3 + exp_bias_correction);
unsigned shift_e = x_e % 3;
// Set x_r = 1.mantissa
double x_r =
FPBits(x_bits.get_mantissa() |
(static_cast<uint64_t>(FPBits::EXP_BIAS) << FPBits::FRACTION_LEN))
.get_val();
// Set a = (-1)^x_sign * 2^(x_e % 3) * (1.mantissa)
uint64_t a_bits = x_bits.uintval() & 0x800F'FFFF'FFFF'FFFF;
a_bits |=
(static_cast<uint64_t>(shift_e + static_cast<unsigned>(FPBits::EXP_BIAS))
<< FPBits::FRACTION_LEN);
double a = FPBits(a_bits).get_val();
// Initial approximation of x_r^(-2/3).
double p = intial_approximation(x_r);
// Look up for 2^(-2*n/3) used for first approximation step.
constexpr double EXP2_M2_OVER_3[3] = {1.0, 0x1.428a2f98d728bp-1,
0x1.965fea53d6e3dp-2};
// x0 is an initial approximation of a^(-2/3) for 1 <= |a| < 8.
// Relative error: < 1.16 * 2^(-21).
double x0 = static_cast<double>(EXP2_M2_OVER_3[shift_e] * p);
// First iteration in double precision.
DoubleDouble a_sq = fputil::exact_mult(a, a);
// h0 = x0^3 * a^2 - 1
DoubleDouble x0_sq = fputil::exact_mult(x0, x0);
DoubleDouble x0_3 = fputil::quick_mult(x0, x0_sq);
double h0 = get_error(x0_3, a_sq);
#ifdef LIBC_MATH_CBRT_SKIP_ACCURATE_PASS
constexpr double REL_ERROR = 0;
#else
constexpr double REL_ERROR = 0x1.0p-51;
#endif // LIBC_MATH_CBRT_SKIP_ACCURATE_PASS
// Taylor polynomial of (1 + h)^(-1/3):
// (1 + h)^(-1/3) = 1 - h/3 + 2 h^2 / 9 - 14 h^3 / 81 + ...
constexpr double ERR_COEFFS[3] = {
-0x1.5555555555555p-2 - REL_ERROR, // -1/3 - relative_error
0x1.c71c71c71c71cp-3, // 2/9
-0x1.61f9add3c0ca4p-3, // -14/81
};
// e0 = -14 * h^2 / 81 + 2 * h / 9 - 1/3 - relative_error.
double e0 = fputil::polyeval(h0, ERR_COEFFS[0], ERR_COEFFS[1], ERR_COEFFS[2]);
double x0_h0 = x0 * h0;
// x1 = x0 (1 - h0/3 + 2 h0^2 / 9 - 14 h0^3 / 81)
// x1 approximate a^(-2/3) with relative errors bounded by:
// | x1 / a^(-2/3) - 1 | < (34/243) h0^4 < h0 * REL_ERROR
DoubleDouble x1_dd{x0_h0 * e0, x0};
// r1 = x1 * a ~ a^(-2/3) * a = a^(1/3).
DoubleDouble r1 = fputil::quick_mult(a, x1_dd);
// Lambda function to update the exponent of the result.
auto update_exponent = [=](double r) -> double {
uint64_t r_m = FPBits(r).uintval() - 0x3FF0'0000'0000'0000;
// Adjust exponent and sign.
uint64_t r_bits =
r_m + (static_cast<uint64_t>(out_e) << FPBits::FRACTION_LEN);
return FPBits(r_bits).get_val();
};
#ifdef LIBC_MATH_CBRT_SKIP_ACCURATE_PASS
// TODO: We probably don't need to use double-double if accurate tests and
// passes are skipped.
return update_exponent(r1.hi + r1.lo);
#else
// Accurate checks and passes.
double r1_lower = r1.hi + r1.lo;
double r1_upper =
r1.hi + fputil::multiply_add(x0_h0, 2.0 * REL_ERROR * a, r1.lo);
// Ziv's accuracy test.
if (LIBC_LIKELY(r1_upper == r1_lower)) {
// Test for exact outputs.
// Check if lower (52 - 17 = 35) bits are 0's.
if (LIBC_UNLIKELY((FPBits(r1_lower).uintval() & 0x0000'0007'FFFF'FFFF) ==
0)) {
double r1_err = (r1_lower - r1.hi) - r1.lo;
if (FPBits(r1_err).abs().get_val() < 0x1.0p69)
fputil::clear_except_if_required(FE_INEXACT);
}
return update_exponent(r1_lower);
}
// Accuracy test failed, perform another Newton iteration.
double x1 = x1_dd.hi + (e0 + REL_ERROR) * x0_h0;
// Second iteration in double-double precision.
// h1 = x1^3 * a^2 - 1.
DoubleDouble x1_sq = fputil::exact_mult(x1, x1);
DoubleDouble x1_3 = fputil::quick_mult(x1, x1_sq);
double h1 = get_error(x1_3, a_sq);
// e1 = -x1*h1/3.
double e1 = h1 * (x1 * -0x1.5555555555555p-2);
// x2 = x1*(1 - h1/3) = x1 + e1 ~ a^(-2/3) with relative errors < 2^-101.
DoubleDouble x2 = fputil::exact_add(x1, e1);
// r2 = a * x2 ~ a * a^(-2/3) = a^(1/3) with relative errors < 2^-100.
DoubleDouble r2 = fputil::quick_mult(a, x2);
double r2_upper = r2.hi + fputil::multiply_add(a, 0x1.0p-102, r2.lo);
double r2_lower = r2.hi + fputil::multiply_add(a, -0x1.0p-102, r2.lo);
// Ziv's accuracy test.
if (LIBC_LIKELY(r2_upper == r2_lower))
return update_exponent(r2_upper);
// TODO: Investigate removing float128 and just list exceptional cases.
// Apply another Newton iteration with ~126-bit accuracy.
Float128 x2_f128 = fputil::quick_add(Float128(x2.hi), Float128(x2.lo));
// x2^3
Float128 x2_3 =
fputil::quick_mul(fputil::quick_mul(x2_f128, x2_f128), x2_f128);
// a^2
Float128 a_sq_f128 = fputil::quick_mul(Float128(a), Float128(a));
// x2^3 * a^2
Float128 x2_3_a_sq = fputil::quick_mul(x2_3, a_sq_f128);
// h2 = x2^3 * a^2 - 1
Float128 h2_f128 = fputil::quick_add(x2_3_a_sq, Float128(-1.0));
double h2 = static_cast<double>(h2_f128);
// t2 = 1 - h2 / 3
Float128 t2 =
fputil::quick_add(Float128(1.0), Float128(h2 * (-0x1.5555555555555p-2)));
// x3 = x2 * (1 - h2 / 3) ~ a^(-2/3)
Float128 x3 = fputil::quick_mul(x2_f128, t2);
// r3 = a * x3 ~ a * a^(-2/3) = a^(1/3)
Float128 r3 = fputil::quick_mul(Float128(a), x3);
// Check for exact cases:
Float128::MantissaType rounding_bits =
r3.mantissa & 0x0000'0000'0000'03FF'FFFF'FFFF'FFFF'FFFF_u128;
double result = static_cast<double>(r3);
if ((rounding_bits < 0x0000'0000'0000'0000'0000'0000'0000'000F_u128) ||
(rounding_bits >= 0x0000'0000'0000'03FF'FFFF'FFFF'FFFF'FFF0_u128)) {
// Output is exact.
r3.mantissa &= 0xFFFF'FFFF'FFFF'FFFF'FFFF'FFFF'FFFF'FFF0_u128;
if (rounding_bits >= 0x0000'0000'0000'03FF'FFFF'FFFF'FFFF'FFF0_u128) {
Float128 tmp{r3.sign, r3.exponent - 123,
0x8000'0000'0000'0000'0000'0000'0000'0000_u128};
Float128 r4 = fputil::quick_add(r3, tmp);
result = static_cast<double>(r4);
} else {
result = static_cast<double>(r3);
}
fputil::clear_except_if_required(FE_INEXACT);
}
return update_exponent(result);
#endif // LIBC_MATH_CBRT_SKIP_ACCURATE_PASS
}
} // namespace LIBC_NAMESPACE_DECL