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Marat Dukhan189ae802019-11-26 11:28:44 -08001// Copyright 2019 Google LLC
2//
3// This source code is licensed under the BSD-style license found in the
4// LICENSE file in the root directory of this source tree.
5
6#include <assert.h>
Marat Dukhan189ae802019-11-26 11:28:44 -08007#include <stddef.h>
8
9#include <arm_neon.h>
10
Marat Dukhanf7814d62020-07-20 23:19:21 -070011#include <xnnpack/common.h>
Marat Dukhan189ae802019-11-26 11:28:44 -080012#include <xnnpack/math-stubs.h>
13
14
Marat Dukhan04fd73a2020-09-24 22:41:47 -070015// Table of exp2(k / 64) values decremented (as integer) by (k << 17), k = 0..63
16extern XNN_INTERNAL const float xnn_table_exp2minus_k_over_64[64];
Marat Dukhan189ae802019-11-26 11:28:44 -080017
18void xnn_math_f32_expminus__neonfma_lut64_p2(
19 size_t n,
20 const float* input,
21 float* output)
22{
23 assert(n % (4 * sizeof(float)) == 0);
24
25 const float32x4_t vmagic_bias = vmovq_n_f32(0x1.800000p23f);
26 // The smallest x for which expf(x) is normalized.
27 const float32x4_t vdenorm_cutoff = vmovq_n_f32(-0x1.5D589Ep6f);
28 const float32x4_t vlog2e_x64 = vmovq_n_f32(0x1.715476p6f);
29 const float32x4_t vminus_ln2_o64_hi = vmovq_n_f32(-0x1.62e43p-7f);
30 const float32x4_t vminus_ln2_o64_lo = vmovq_n_f32(0x1.05c61p-35f);
31
32 const float32x4_t vc2 = vmovq_n_f32(0x1.FFFF0Ap-2f);
33
34 const int32x4_t vindex_mask = vmovq_n_s32(INT32_C(0x3F));
35
36 for (; n != 0; n -= 4 * sizeof(float)) {
37 const float32x4_t vx = vld1q_f32(input); input += 4;
38
39 // Compute reduced argument n := round(x * 64 / log(2)).
40 // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing
41 // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
42 // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e.
43 // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0]
44 // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the
45 // algorithm.
46 float32x4_t vn = vfmaq_f32(vmagic_bias, vx, vlog2e_x64);
47
48 // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized,
49 // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where
50 // e := int(n / 64). We create s in two steps:
Marat Dukhanf7814d62020-07-20 23:19:21 -070051 // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) from the table using the 6 low bits of n, as integer. Note that the
Marat Dukhan189ae802019-11-26 11:28:44 -080052 // fetched values are in the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
53 // 2. Adjust fecthed value by addition of e to its floating-point exponent. The result is always a normalized
54 // number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0,
55 // and thus the adjusted exponent is not lower than -126.
56 //
Marat Dukhan04fd73a2020-09-24 22:41:47 -070057 // Shift bits 6:14 into 23:31 (position of floating-point exponent).
58 const int32x4_t ve = vshlq_n_s32(vreinterpretq_s32_f32(vn), 17);
Marat Dukhan189ae802019-11-26 11:28:44 -080059
60 // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64).
Marat Dukhan272139e2020-09-21 01:01:31 -070061 const uint64x2_t vidx = vreinterpretq_u64_s32(vshlq_n_s32(vandq_s32(vreinterpretq_s32_f32(vn), vindex_mask), 2));
Marat Dukhan189ae802019-11-26 11:28:44 -080062 const uint64_t vidx01 = vgetq_lane_u64(vidx, 0);
63 const uint64_t vidx23 = vgetq_lane_u64(vidx, 1);
Marat Dukhan04fd73a2020-09-24 22:41:47 -070064 float32x2_t vl01 = vld1_dup_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) vidx01));
65 float32x2_t vl23 = vld1_dup_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) vidx23));
66 vl01 = vld1_lane_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) (vidx01 >> 32)), vl01, 1);
67 vl23 = vld1_lane_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) (vidx23 >> 32)), vl23, 1);
Marat Dukhan189ae802019-11-26 11:28:44 -080068 const float32x4_t vl = vcombine_f32(vl01, vl23);
Marat Dukhanf7814d62020-07-20 23:19:21 -070069 // Adjust exponent of the value l fetched from the table to get the final s value.
Marat Dukhan189ae802019-11-26 11:28:44 -080070 const float32x4_t vs = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl), ve));
71
72 // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number.
73 vn = vsubq_f32(vn, vmagic_bias);
74
75 // Compute reduced argument t := x - n * log(2) / 64.
76 // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy.
77 float32x4_t vt = vfmaq_f32(vx, vn, vminus_ln2_o64_hi);
78 vt = vfmaq_f32(vt, vn, vminus_ln2_o64_lo);
79
Marat Dukhan102a7392020-11-20 01:18:10 -080080 // Compute degree-2 polynomial approximation for exp(t) on [-log(2)/128, log(2)/128].
Marat Dukhan189ae802019-11-26 11:28:44 -080081 float32x4_t vp = vmulq_f32(vt, vc2);
82 vp = vfmaq_f32(vt, vt, vp);
83
84 // Reconstruct the final f value:
85 // f = s * (1 + t * (1 + t * c2))
86 // = s * (1 + t + t * (t * c2))
87 // = s + s * (t + t * (t * c2))
88 // = s + s * p
89 float32x4_t vf = vfmaq_f32(vs, vs, vp);
90
91 // For inputs below denormal cutoff, replace output with +0.0f.
92 // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
93 vf = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcltq_f32(vx, vdenorm_cutoff)));
94 vst1q_f32(output, vf); output += 4;
95 }
96}