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// Copyright 2019 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#include <assert.h>
#include <math.h>
#include <stddef.h>
#include <arm_neon.h>
#include <xnnpack/math-stubs.h>
// Table of exp2(k / 64) values, k = 0..63
static const float exp2_table[64] = {
0x1.000000p+0f, 0x1.02C9A4p+0f, 0x1.059B0Ep+0f, 0x1.087452p+0f,
0x1.0B5586p+0f, 0x1.0E3EC4p+0f, 0x1.11301Ep+0f, 0x1.1429AAp+0f,
0x1.172B84p+0f, 0x1.1A35BEp+0f, 0x1.1D4874p+0f, 0x1.2063B8p+0f,
0x1.2387A6p+0f, 0x1.26B456p+0f, 0x1.29E9E0p+0f, 0x1.2D285Ap+0f,
0x1.306FE0p+0f, 0x1.33C08Cp+0f, 0x1.371A74p+0f, 0x1.3A7DB4p+0f,
0x1.3DEA64p+0f, 0x1.4160A2p+0f, 0x1.44E086p+0f, 0x1.486A2Cp+0f,
0x1.4BFDAEp+0f, 0x1.4F9B28p+0f, 0x1.5342B6p+0f, 0x1.56F474p+0f,
0x1.5AB07Ep+0f, 0x1.5E76F2p+0f, 0x1.6247ECp+0f, 0x1.662388p+0f,
0x1.6A09E6p+0f, 0x1.6DFB24p+0f, 0x1.71F75Ep+0f, 0x1.75FEB6p+0f,
0x1.7A1148p+0f, 0x1.7E2F34p+0f, 0x1.82589Ap+0f, 0x1.868D9Ap+0f,
0x1.8ACE54p+0f, 0x1.8F1AEAp+0f, 0x1.93737Cp+0f, 0x1.97D82Ap+0f,
0x1.9C4918p+0f, 0x1.A0C668p+0f, 0x1.A5503Cp+0f, 0x1.A9E6B6p+0f,
0x1.AE89FAp+0f, 0x1.B33A2Cp+0f, 0x1.B7F770p+0f, 0x1.BCC1EAp+0f,
0x1.C199BEp+0f, 0x1.C67F12p+0f, 0x1.CB720Ep+0f, 0x1.D072D4p+0f,
0x1.D5818Ep+0f, 0x1.DA9E60p+0f, 0x1.DFC974p+0f, 0x1.E502EEp+0f,
0x1.EA4AFAp+0f, 0x1.EFA1BEp+0f, 0x1.F50766p+0f, 0x1.FA7C18p+0f,
};
void xnn_math_f32_exp__neonfma_lut64_p2(
size_t n,
const float* input,
float* output)
{
assert(n % (4 * sizeof(float)) == 0);
const float32x4_t vmagic_bias = vmovq_n_f32(0x1.800000p23f);
// The smallest x for which expf(x) is non-zero.
const float32x4_t vzero_cutoff = vmovq_n_f32(-0x1.9FE368p6f);
// The largest x for which expf(x) is finite.
const float32x4_t vinf_cutoff = vmovq_n_f32(0x1.62E42Ep6f);
const float32x4_t vlog2e_x64 = vmovq_n_f32(0x1.715476p6f);
const float32x4_t vminus_ln2_o64_hi = vmovq_n_f32(-0x1.62e43p-7f);
const float32x4_t vminus_ln2_o64_lo = vmovq_n_f32(0x1.05c61p-35f);
const float32x4_t vplus_inf = vmovq_n_f32(INFINITY);
const float32x4_t vc2 = vmovq_n_f32(0x1.FFFF0Ap-2f);
const int32x4_t vmin_exponent = vmovq_n_s32(INT32_C(0xC1000000));
const int32x4_t vmax_exponent = vmovq_n_s32(INT32_C(0x3F800000));
const int32x4_t vdefault_exponent = vmax_exponent;
const int32x4_t vindex_mask = vmovq_n_s32(INT32_C(0x3F));
for (; n != 0; n -= 4 * sizeof(float)) {
const float32x4_t vx = vld1q_f32(input); input += 4;
// Compute reduced argument n := round(x * 64 / log(2)).
// We do it by adding a large number (magic bias), which cause rounding of result to an integer, then subtracing the
// large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
// The trick with adding large number is valid only within certain bounds (|x| <= 2**22), but thats ok, because
// inputs outside of [-103.97207, 88.72283] underflow or overflow expf(x) anyway. We fixup the result for such
// inputs at the very end of the algorithm.
float32x4_t vn = vfmaq_f32(vmagic_bias, vx, vlog2e_x64);
// Create two floating-point numbers, sn (scale, normal) and so (scale, overflow) such that sn * so == 2**n
// for inputs which don't cause overflow, i.e. -103.97207 <= x <= 88.72283, and -150 <= n <= 128 accordingly.
// We need to use two numbers rather than one because a normalized single-precision exponent must be in [-127, 126]
// range, which is insufficient to cover [-150, 128] range of n.
// - When n is within [-127, 126], sn == 2**n and so == 1.0.
// - When n < -127, sn == 2**(-127) and so == 2**(n + 127).
// - When n > 126, sn == 2**126 and so == 2**(n - 126).
// While we explicitly compute sn, the so is fused into the value l fetched from a table by adjusting its exponential.
int32x4_t veo = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn), vmovq_n_s32(INT32_C(0x3F))), 17);
int32x4_t ven = vmaxq_s32(veo, vmin_exponent);
ven = vminq_s32(ven, vmax_exponent);
veo = vsubq_s32(veo, ven);
const float32x4_t vsn = vreinterpretq_f32_s32(vaddq_s32(ven, vdefault_exponent));
// Use the low 6 bits of n (as integer) for table lookup.
const uint64x2_t vidx = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn), vindex_mask));
const uint64_t vidx01 = vgetq_lane_u64(vidx, 0);
const uint64_t vidx23 = vgetq_lane_u64(vidx, 1);
float32x2_t vl01 = vld1_dup_f32(&exp2_table[(uint32_t) vidx01]);
float32x2_t vl23 = vld1_dup_f32(&exp2_table[(uint32_t) vidx23]);
vl01 = vld1_lane_f32(&exp2_table[(uint32_t) (vidx01 >> 32)], vl01, 1);
vl23 = vld1_lane_f32(&exp2_table[(uint32_t) (vidx23 >> 32)], vl23, 1);
float32x4_t vl = vcombine_f32(vl01, vl23);
// Fuse so into the value l fetched from a table by adjusting its exponential.
vl = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl), veo));
// Subtract the large number back to get final n := round(x * 64 / log(2)).
vn = vsubq_f32(vn, vmagic_bias);
// Compute reduced argument t := x - n * log(2) / 64.
// Use Cody-Waite range reduction method (note two constants to represent log(2) / 64) to improve accuracy.
float32x4_t vt = vfmaq_f32(vx, vn, vminus_ln2_o64_hi);
vt = vfmaq_f32(vt, vn, vminus_ln2_o64_lo);
// Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128].
float32x4_t vp = vmulq_f32(vt, vc2);
vp = vfmaq_f32(vt, vt, vp);
// Reconstruct the final f value:
// f = sn * (so * l) * (1 + t * (1 + t * c2))
// = sn * (so * l) * (1 + t + t * (t * c2))
// = sn * ((so * l) + (so * l) * (t + t * (t * c2)))
float32x4_t vf = vfmaq_f32(vl, vl, vp);
vf = vmulq_f32(vf, vsn);
// For inputs below zero cutoff, replace output with +0.0f.
// Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
vf = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcltq_f32(vx, vzero_cutoff)));
// For inputs above inf cutoff, replace output with +inf.
// Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
vf = vbslq_f32(vcgtq_f32(vx, vinf_cutoff), vplus_inf, vf);
vst1q_f32(output, vf); output += 4;
}
}