xref: /aosp_15_r20/external/XNNPACK/src/math/expminus-f32-scalar-rr2-lut2048-p1.c (revision 4bdc94577ba0e567308109d787f7fec7b531ce36)
1 // 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>
7 #include <stddef.h>
8 
9 #include <xnnpack/common.h>
10 #include <xnnpack/math.h>
11 #include <xnnpack/math-stubs.h>
12 
13 
14 // Table of exp2(k / 2048) values decremented (as integer) by (k << 12), k = 0..2048
15 extern XNN_INTERNAL const uint32_t xnn_table_exp2minus_k_over_2048[2048];
16 
xnn_math_f32_expminus__scalar_rr2_lut2048_p1(size_t n,const float * input,float * output)17 void xnn_math_f32_expminus__scalar_rr2_lut2048_p1(
18     size_t n,
19     const float* input,
20     float* output)
21 {
22   assert(n % sizeof(float) == 0);
23 
24   // Large number such that ulp(magic bias) == exp2(-11)
25   const float vmagic_bias = 0x1.800000p12f;
26   const float vlog2e  = 0x1.715476p0f;
27   // Mask for the lowest 11 bits
28   const uint32_t vindex_mask = UINT32_C(0x7FF);
29   // Last 18 bits are zeroes
30   const float vminus_ln2_hi = -0x1.600000p-1f;
31   const float vminus_ln2_lo = -0x1.7217F8p-8f;
32   // Coefficient of polynomial approximation
33   //   exp(t) ~ 1 + t * c1
34   // on [-log(2)/2048, log(2)/2048]
35   const float vc1 = 0x1.FFFFFEp-1f;
36   // The smallest x for which expf(x) is normalized.
37   const float vdenorm_cutoff = -0x1.5D589Ep6f;
38 
39   for (; n != 0; n -= sizeof(float)) {
40     const float vx = *input++;
41 
42     // Compute reduced argument n := round(x / log(2), 11).
43     // We do it by adding a large number (magic bias), which cause rounding of the result to 11 fractional bits, then
44     // subtracing the large number back. The trick with adding large number is valid only within certain bounds
45     // (|x / log(2)| <= 2**11, i.e. |x| <= 0x1.62E43p+10 = 1419.5654296875), but that is acceptable, because inputs x
46     // outside of [-87.336544, 0] underflow expf(x). We fixup the result for such inputs at the very end of the
47     // algorithm.
48     float vn = vx * vlog2e + vmagic_bias;
49 
50     // Create a floating-point number s (scale) such that s := 2**n for such inputs that expf(x) is normalized, i.e.
51     // -87.336544 <= x <= 0. As n has 11 fractional bits, we split s == 2**n = 2**int(n) * 2**frac(n). We create s in
52     // two steps:
53     // 1. Fetch 2**frac(n) from the table using the 11 low bits of n, as integer. Note that the fetched values are in
54     //    the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
55     // 2. Adjust fecthed value by addition of int(n) to its floating-point exponent. The result is always a normalized
56     //    number, because for -87.33642 <= x <= 0 (inputs for which expf(x) is normalized) we have -126 <= int(n) <= 0,
57     //    and thus the adjusted exponent is not lower than -126.
58     //
59     // Shift bits 11:19 into 23:31 (position of floating-point exponent).
60     const uint32_t ve = float_as_uint32(vn) << 12;
61 
62     // Use bits 0:11 of n, as integer, as an index for table lookup of l := 2**frac(n).
63     const uint32_t vidx = float_as_uint32(vn) & vindex_mask;
64     // Adjust exponent of the value l fetched from the table to get the final s value.
65     const float vs = uint32_as_float(xnn_table_exp2minus_k_over_2048[vidx] + ve);
66 
67     // Subtract the large number back to get final n := round(x / log(2), 11) as a floating-point number.
68     vn -= vmagic_bias;
69 
70     // Compute reduced argument t := x - n * log(2)
71     // Use Cody-Waite range reduction method (note the two constants representing log(2)) to improve accuracy.
72     float vt = vn * vminus_ln2_hi + vx;
73     vt = vn * vminus_ln2_lo + vt;
74 
75     // Compute degree-1 polynomial approximation for exp(t) on [-log(2)/2048, log(2)/2048].
76     //   P(t) = 1 + t * c1 = 1 + t * c1 = 1 + p
77     const float vp = vt * vc1;
78 
79     // Reconstruct the exp(x) value:
80     //   exp(x) = s * (1 + t * c1)
81     //          = s * (1 + p)
82     //          = s + s * p
83     float vf = vp * vs + vs;
84 
85     // For inputs below denormal cutoff, replace output with +0.0f.
86     // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
87     if XNN_UNPREDICTABLE(vx < vdenorm_cutoff) {
88       vf = 0.0f;
89     }
90 
91     *output++ = vf;
92   }
93 }
94