1 | use crate::Adler32; |
2 | use std::ops::{AddAssign, MulAssign, RemAssign}; |
3 | |
4 | impl Adler32 { |
5 | pub(crate) fn compute(&mut self, bytes: &[u8]) { |
6 | // The basic algorithm is, for every byte: |
7 | // a = (a + byte) % MOD |
8 | // b = (b + a) % MOD |
9 | // where MOD = 65521. |
10 | // |
11 | // For efficiency, we can defer the `% MOD` operations as long as neither a nor b overflows: |
12 | // - Between calls to `write`, we ensure that a and b are always in range 0..MOD. |
13 | // - We use 32-bit arithmetic in this function. |
14 | // - Therefore, a and b must not increase by more than 2^32-MOD without performing a `% MOD` |
15 | // operation. |
16 | // |
17 | // According to Wikipedia, b is calculated as follows for non-incremental checksumming: |
18 | // b = n×D1 + (n−1)×D2 + (n−2)×D3 + ... + Dn + n*1 (mod 65521) |
19 | // Where n is the number of bytes and Di is the i-th Byte. We need to change this to account |
20 | // for the previous values of a and b, as well as treat every input Byte as being 255: |
21 | // b_inc = n×255 + (n-1)×255 + ... + 255 + n*65520 |
22 | // Or in other words: |
23 | // b_inc = n*65520 + n(n+1)/2*255 |
24 | // The max chunk size is thus the largest value of n so that b_inc <= 2^32-65521. |
25 | // 2^32-65521 = n*65520 + n(n+1)/2*255 |
26 | // Plugging this into an equation solver since I can't math gives n = 5552.18..., so 5552. |
27 | // |
28 | // On top of the optimization outlined above, the algorithm can also be parallelized with a |
29 | // bit more work: |
30 | // |
31 | // Note that b is a linear combination of a vector of input bytes (D1, ..., Dn). |
32 | // |
33 | // If we fix some value k<N and rewrite indices 1, ..., N as |
34 | // |
35 | // 1_1, 1_2, ..., 1_k, 2_1, ..., 2_k, ..., (N/k)_k, |
36 | // |
37 | // then we can express a and b in terms of sums of smaller sequences kb and ka: |
38 | // |
39 | // ka(j) := D1_j + D2_j + ... + D(N/k)_j where j <= k |
40 | // kb(j) := (N/k)*D1_j + (N/k-1)*D2_j + ... + D(N/k)_j where j <= k |
41 | // |
42 | // a = ka(1) + ka(2) + ... + ka(k) + 1 |
43 | // b = k*(kb(1) + kb(2) + ... + kb(k)) - 1*ka(2) - ... - (k-1)*ka(k) + N |
44 | // |
45 | // We use this insight to unroll the main loop and process k=4 bytes at a time. |
46 | // The resulting code is highly amenable to SIMD acceleration, although the immediate speedups |
47 | // stem from increased pipeline parallelism rather than auto-vectorization. |
48 | // |
49 | // This technique is described in-depth (here:)[https://software.intel.com/content/www/us/\ |
50 | // en/develop/articles/fast-computation-of-fletcher-checksums.html] |
51 | |
52 | const MOD: u32 = 65521; |
53 | const CHUNK_SIZE: usize = 5552 * 4; |
54 | |
55 | let mut a = u32::from(self.a); |
56 | let mut b = u32::from(self.b); |
57 | let mut a_vec = U32X4([0; 4]); |
58 | let mut b_vec = a_vec; |
59 | |
60 | let (bytes, remainder) = bytes.split_at(bytes.len() - bytes.len() % 4); |
61 | |
62 | // iterate over 4 bytes at a time |
63 | let chunk_iter = bytes.chunks_exact(CHUNK_SIZE); |
64 | let remainder_chunk = chunk_iter.remainder(); |
65 | for chunk in chunk_iter { |
66 | for byte_vec in chunk.chunks_exact(4) { |
67 | let val = U32X4::from(byte_vec); |
68 | a_vec += val; |
69 | b_vec += a_vec; |
70 | } |
71 | |
72 | b += CHUNK_SIZE as u32 * a; |
73 | a_vec %= MOD; |
74 | b_vec %= MOD; |
75 | b %= MOD; |
76 | } |
77 | // special-case the final chunk because it may be shorter than the rest |
78 | for byte_vec in remainder_chunk.chunks_exact(4) { |
79 | let val = U32X4::from(byte_vec); |
80 | a_vec += val; |
81 | b_vec += a_vec; |
82 | } |
83 | b += remainder_chunk.len() as u32 * a; |
84 | a_vec %= MOD; |
85 | b_vec %= MOD; |
86 | b %= MOD; |
87 | |
88 | // combine the sub-sum results into the main sum |
89 | b_vec *= 4; |
90 | b_vec.0[1] += MOD - a_vec.0[1]; |
91 | b_vec.0[2] += (MOD - a_vec.0[2]) * 2; |
92 | b_vec.0[3] += (MOD - a_vec.0[3]) * 3; |
93 | for &av in a_vec.0.iter() { |
94 | a += av; |
95 | } |
96 | for &bv in b_vec.0.iter() { |
97 | b += bv; |
98 | } |
99 | |
100 | // iterate over the remaining few bytes in serial |
101 | for &byte in remainder.iter() { |
102 | a += u32::from(byte); |
103 | b += a; |
104 | } |
105 | |
106 | self.a = (a % MOD) as u16; |
107 | self.b = (b % MOD) as u16; |
108 | } |
109 | } |
110 | |
111 | #[derive (Copy, Clone)] |
112 | struct U32X4([u32; 4]); |
113 | |
114 | impl U32X4 { |
115 | #[inline ] |
116 | fn from(bytes: &[u8]) -> Self { |
117 | U32X4([ |
118 | u32::from(bytes[0]), |
119 | u32::from(bytes[1]), |
120 | u32::from(bytes[2]), |
121 | u32::from(bytes[3]), |
122 | ]) |
123 | } |
124 | } |
125 | |
126 | impl AddAssign<Self> for U32X4 { |
127 | #[inline ] |
128 | fn add_assign(&mut self, other: Self) { |
129 | // Implement this in a primitive manner to help out the compiler a bit. |
130 | self.0[0] += other.0[0]; |
131 | self.0[1] += other.0[1]; |
132 | self.0[2] += other.0[2]; |
133 | self.0[3] += other.0[3]; |
134 | } |
135 | } |
136 | |
137 | impl RemAssign<u32> for U32X4 { |
138 | #[inline ] |
139 | fn rem_assign(&mut self, quotient: u32) { |
140 | self.0[0] %= quotient; |
141 | self.0[1] %= quotient; |
142 | self.0[2] %= quotient; |
143 | self.0[3] %= quotient; |
144 | } |
145 | } |
146 | |
147 | impl MulAssign<u32> for U32X4 { |
148 | #[inline ] |
149 | fn mul_assign(&mut self, rhs: u32) { |
150 | self.0[0] *= rhs; |
151 | self.0[1] *= rhs; |
152 | self.0[2] *= rhs; |
153 | self.0[3] *= rhs; |
154 | } |
155 | } |
156 | |