lexical_parse_float/lemire.rs
1//! Implementation of the Eisel-Lemire algorithm.
2//!
3//! This is adapted from [fast-float-rust](https://github.com/aldanor/fast-float-rust),
4//! a port of [fast_float](https://github.com/fastfloat/fast_float) to Rust.
5
6#![cfg(not(feature = "compact"))]
7#![doc(hidden)]
8
9use crate::float::{ExtendedFloat80, LemireFloat};
10use crate::number::Number;
11use crate::shared;
12use crate::table::{LARGEST_POWER_OF_FIVE, POWER_OF_FIVE_128, SMALLEST_POWER_OF_FIVE};
13
14/// Ensure truncation of digits doesn't affect our computation, by doing 2
15/// passes.
16#[must_use]
17#[inline(always)]
18pub fn lemire<F: LemireFloat>(num: &Number, lossy: bool) -> ExtendedFloat80 {
19 // If significant digits were truncated, then we can have rounding error
20 // only if `mantissa + 1` produces a different result. We also avoid
21 // redundantly using the Eisel-Lemire algorithm if it was unable to
22 // correctly round on the first pass.
23 let mut fp = compute_float::<F>(num.exponent, num.mantissa, lossy);
24 if !lossy
25 && num.many_digits
26 && fp.exp >= 0
27 && fp != compute_float::<F>(num.exponent, num.mantissa + 1, false)
28 {
29 // Need to re-calculate, since the previous values are rounded
30 // when the slow path algorithm expects a normalized extended float.
31 fp = compute_error::<F>(num.exponent, num.mantissa);
32 }
33 fp
34}
35
36/// Compute a float using an extended-precision representation.
37///
38/// Fast conversion of a the significant digits and decimal exponent
39/// a float to a extended representation with a binary float. This
40/// algorithm will accurately parse the vast majority of cases,
41/// and uses a 128-bit representation (with a fallback 192-bit
42/// representation).
43///
44/// This algorithm scales the exponent by the decimal exponent
45/// using pre-computed powers-of-5, and calculates if the
46/// representation can be unambiguously rounded to the nearest
47/// machine float. Near-halfway cases are not handled here,
48/// and are represented by a negative, biased binary exponent.
49///
50/// The algorithm is described in detail in "Daniel Lemire, Number Parsing
51/// at a Gigabyte per Second" in section 5, "Fast Algorithm", and
52/// section 6, "Exact Numbers And Ties", available online:
53/// <https://arxiv.org/abs/2101.11408.pdf>.
54#[inline]
55#[must_use]
56#[allow(clippy::missing_inline_in_public_items)] // reason="public for testing only"
57pub fn compute_float<F: LemireFloat>(q: i64, mut w: u64, lossy: bool) -> ExtendedFloat80 {
58 let fp_zero = ExtendedFloat80 {
59 mant: 0,
60 exp: 0,
61 };
62 let fp_inf = ExtendedFloat80 {
63 mant: 0,
64 exp: F::INFINITE_POWER,
65 };
66
67 // Short-circuit if the value can only be a literal 0 or infinity.
68 if w == 0 || q < F::SMALLEST_POWER_OF_TEN as i64 {
69 return fp_zero;
70 } else if q > F::LARGEST_POWER_OF_TEN as i64 {
71 return fp_inf;
72 }
73 // Normalize our significant digits, so the most-significant bit is set.
74 let lz = w.leading_zeros() as i32;
75 w <<= lz;
76 let (lo, hi) = compute_product_approx(q, w, F::MANTISSA_SIZE as usize + 3);
77 if !lossy && lo == 0xFFFF_FFFF_FFFF_FFFF {
78 // If we have failed to approximate `w x 5^-q` with our 128-bit value.
79 // Since the addition of 1 could lead to an overflow which could then
80 // round up over the half-way point, this can lead to improper rounding
81 // of a float.
82 //
83 // However, this can only occur if `q ∈ [-27, 55]`. The upper bound of q
84 // is 55 because `5^55 < 2^128`, however, this can only happen if `5^q > 2^64`,
85 // since otherwise the product can be represented in 64-bits, producing
86 // an exact result. For negative exponents, rounding-to-even can
87 // only occur if `5^-q < 2^64`.
88 //
89 // For detailed explanations of rounding for negative exponents, see
90 // <https://arxiv.org/pdf/2101.11408.pdf#section.9.1>. For detailed
91 // explanations of rounding for positive exponents, see
92 // <https://arxiv.org/pdf/2101.11408.pdf#section.8>.
93 let inside_safe_exponent = (-27..=55).contains(&q);
94 if !inside_safe_exponent {
95 return compute_error_scaled::<F>(q, hi, lz);
96 }
97 }
98 let upperbit = (hi >> 63) as i32;
99 let mut mantissa = hi >> (upperbit + 64 - F::MANTISSA_SIZE - 3);
100 let mut power2 = power(q as i32) + upperbit - lz - F::MINIMUM_EXPONENT;
101 if power2 <= 0 {
102 if -power2 + 1 >= 64 {
103 // Have more than 64 bits below the minimum exponent, must be 0.
104 return fp_zero;
105 }
106 // Have a subnormal value.
107 mantissa >>= -power2 + 1;
108 mantissa += mantissa & 1;
109 mantissa >>= 1;
110 power2 = (mantissa >= (1_u64 << F::MANTISSA_SIZE)) as i32;
111 return ExtendedFloat80 {
112 mant: mantissa,
113 exp: power2,
114 };
115 }
116 // Need to handle rounding ties. Normally, we need to round up,
117 // but if we fall right in between and and we have an even basis, we
118 // need to round down.
119 //
120 // This will only occur if:
121 // 1. The lower 64 bits of the 128-bit representation is 0. IE, `5^q` fits in
122 // single 64-bit word.
123 // 2. The least-significant bit prior to truncated mantissa is odd.
124 // 3. All the bits truncated when shifting to mantissa bits + 1 are 0.
125 //
126 // Or, we may fall between two floats: we are exactly halfway.
127 if lo <= 1
128 && q >= F::MIN_EXPONENT_ROUND_TO_EVEN as i64
129 && q <= F::MAX_EXPONENT_ROUND_TO_EVEN as i64
130 && mantissa & 3 == 1
131 && (mantissa << (upperbit + 64 - F::MANTISSA_SIZE - 3)) == hi
132 {
133 // Zero the lowest bit, so we don't round up.
134 mantissa &= !1_u64;
135 }
136 // Round-to-even, then shift the significant digits into place.
137 mantissa += mantissa & 1;
138 mantissa >>= 1;
139 if mantissa >= (2_u64 << F::MANTISSA_SIZE) {
140 // Rounding up overflowed, so the carry bit is set. Set the
141 // mantissa to 1 (only the implicit, hidden bit is set) and
142 // increase the exponent.
143 mantissa = 1_u64 << F::MANTISSA_SIZE;
144 power2 += 1;
145 }
146 // Zero out the hidden bit.
147 mantissa &= !(1_u64 << F::MANTISSA_SIZE);
148 if power2 >= F::INFINITE_POWER {
149 // Exponent is above largest normal value, must be infinite.
150 return fp_inf;
151 }
152 ExtendedFloat80 {
153 mant: mantissa,
154 exp: power2,
155 }
156}
157
158/// Fallback algorithm to calculate the non-rounded representation.
159/// This calculates the extended representation, and then normalizes
160/// the resulting representation, so the high bit is set.
161#[must_use]
162#[inline(always)]
163pub fn compute_error<F: LemireFloat>(q: i64, mut w: u64) -> ExtendedFloat80 {
164 let lz = w.leading_zeros() as i32;
165 w <<= lz;
166 let hi = compute_product_approx(q, w, F::MANTISSA_SIZE as usize + 3).1;
167 compute_error_scaled::<F>(q, hi, lz)
168}
169
170/// Compute the error from a mantissa scaled to the exponent.
171#[must_use]
172#[inline(always)]
173pub const fn compute_error_scaled<F: LemireFloat>(q: i64, mut w: u64, lz: i32) -> ExtendedFloat80 {
174 // Want to normalize the float, but this is faster than ctlz on most
175 // architectures.
176 let hilz = (w >> 63) as i32 ^ 1;
177 w <<= hilz;
178 let power2 = power(q as i32) + F::EXPONENT_BIAS - hilz - lz - 62;
179
180 ExtendedFloat80 {
181 mant: w,
182 exp: power2 + shared::INVALID_FP,
183 }
184}
185
186/// Calculate a base 2 exponent from a decimal exponent.
187/// This uses a pre-computed integer approximation for
188/// log2(10), where 217706 / 2^16 is accurate for the
189/// entire range of non-finite decimal exponents.
190#[inline(always)]
191const fn power(q: i32) -> i32 {
192 (q.wrapping_mul(152_170 + 65536) >> 16) + 63
193}
194
195#[inline(always)]
196const fn full_multiplication(a: u64, b: u64) -> (u64, u64) {
197 let r = (a as u128) * (b as u128);
198 (r as u64, (r >> 64) as u64)
199}
200
201// This will compute or rather approximate `w * 5**q` and return a pair of
202// 64-bit words approximating the result, with the "high" part corresponding to
203// the most significant bits and the low part corresponding to the least
204// significant bits.
205#[inline]
206fn compute_product_approx(q: i64, w: u64, precision: usize) -> (u64, u64) {
207 debug_assert!(q >= SMALLEST_POWER_OF_FIVE as i64, "must be within our required pow5 range");
208 debug_assert!(q <= LARGEST_POWER_OF_FIVE as i64, "must be within our required pow5 range");
209 debug_assert!(precision <= 64, "requires a 64-bit or smaller float");
210
211 let mask = if precision < 64 {
212 0xFFFF_FFFF_FFFF_FFFF_u64 >> precision
213 } else {
214 0xFFFF_FFFF_FFFF_FFFF_u64
215 };
216
217 // `5^q < 2^64`, then the multiplication always provides an exact value.
218 // That means whenever we need to round ties to even, we always have
219 // an exact value.
220 let index = (q - SMALLEST_POWER_OF_FIVE as i64) as usize;
221 let (lo5, hi5) = POWER_OF_FIVE_128[index];
222 // Only need one multiplication as long as there is 1 zero but
223 // in the explicit mantissa bits, +1 for the hidden bit, +1 to
224 // determine the rounding direction, +1 for if the computed
225 // product has a leading zero.
226 let (mut first_lo, mut first_hi) = full_multiplication(w, lo5);
227 if first_hi & mask == mask {
228 // Need to do a second multiplication to get better precision
229 // for the lower product. This will always be exact
230 // where q is < 55, since 5^55 < 2^128. If this wraps,
231 // then we need to need to round up the hi product.
232 let (_, second_hi) = full_multiplication(w, hi5);
233 first_lo = first_lo.wrapping_add(second_hi);
234 if second_hi > first_lo {
235 first_hi += 1;
236 }
237 }
238 (first_lo, first_hi)
239}