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use crate::Adler32;
use std::ops::{AddAssign, MulAssign, RemAssign};
impl Adler32 {
pub(crate) fn compute(&mut self, bytes: &[u8]) {
// The basic algorithm is, for every byte:
// a = (a + byte) % MOD
// b = (b + a) % MOD
// where MOD = 65521.
//
// For efficiency, we can defer the `% MOD` operations as long as neither a nor b overflows:
// - Between calls to `write`, we ensure that a and b are always in range 0..MOD.
// - We use 32-bit arithmetic in this function.
// - Therefore, a and b must not increase by more than 2^32-MOD without performing a `% MOD`
// operation.
//
// According to Wikipedia, b is calculated as follows for non-incremental checksumming:
// b = n×D1 + (n−1)×D2 + (n−2)×D3 + ... + Dn + n*1 (mod 65521)
// Where n is the number of bytes and Di is the i-th Byte. We need to change this to account
// for the previous values of a and b, as well as treat every input Byte as being 255:
// b_inc = n×255 + (n-1)×255 + ... + 255 + n*65520
// Or in other words:
// b_inc = n*65520 + n(n+1)/2*255
// The max chunk size is thus the largest value of n so that b_inc <= 2^32-65521.
// 2^32-65521 = n*65520 + n(n+1)/2*255
// Plugging this into an equation solver since I can't math gives n = 5552.18..., so 5552.
//
// On top of the optimization outlined above, the algorithm can also be parallelized with a
// bit more work:
//
// Note that b is a linear combination of a vector of input bytes (D1, ..., Dn).
//
// If we fix some value k<N and rewrite indices 1, ..., N as
//
// 1_1, 1_2, ..., 1_k, 2_1, ..., 2_k, ..., (N/k)_k,
//
// then we can express a and b in terms of sums of smaller sequences kb and ka:
//
// ka(j) := D1_j + D2_j + ... + D(N/k)_j where j <= k
// kb(j) := (N/k)*D1_j + (N/k-1)*D2_j + ... + D(N/k)_j where j <= k
//
// a = ka(1) + ka(2) + ... + ka(k) + 1
// b = k*(kb(1) + kb(2) + ... + kb(k)) - 1*ka(2) - ... - (k-1)*ka(k) + N
//
// We use this insight to unroll the main loop and process k=4 bytes at a time.
// The resulting code is highly amenable to SIMD acceleration, although the immediate speedups
// stem from increased pipeline parallelism rather than auto-vectorization.
//
// en/develop/articles/fast-computation-of-fletcher-checksums.html]
const MOD: u32 = 65521;
const CHUNK_SIZE: usize = 5552 * 4;
let mut a = u32::from(self.a);
let mut b = u32::from(self.b);
let mut a_vec = U32X4([0; 4]);
let mut b_vec = a_vec;
let (bytes, remainder) = bytes.split_at(bytes.len() - bytes.len() % 4);
// iterate over 4 bytes at a time
let chunk_iter = bytes.chunks_exact(CHUNK_SIZE);
let remainder_chunk = chunk_iter.remainder();
for chunk in chunk_iter {
for byte_vec in chunk.chunks_exact(4) {
let val = U32X4::from(byte_vec);
a_vec += val;
b_vec += a_vec;
}
b += CHUNK_SIZE as u32 * a;
a_vec %= MOD;
b_vec %= MOD;
b %= MOD;
}
// special-case the final chunk because it may be shorter than the rest
for byte_vec in remainder_chunk.chunks_exact(4) {
let val = U32X4::from(byte_vec);
a_vec += val;
b_vec += a_vec;
}
b += remainder_chunk.len() as u32 * a;
a_vec %= MOD;
b_vec %= MOD;
b %= MOD;
// combine the sub-sum results into the main sum
b_vec *= 4;
b_vec.0[1] += MOD - a_vec.0[1];
b_vec.0[2] += (MOD - a_vec.0[2]) * 2;
b_vec.0[3] += (MOD - a_vec.0[3]) * 3;
for &av in a_vec.0.iter() {
a += av;
}
for &bv in b_vec.0.iter() {
b += bv;
}
// iterate over the remaining few bytes in serial
for &byte in remainder.iter() {
a += u32::from(byte);
b += a;
}
self.a = (a % MOD) as u16;
self.b = (b % MOD) as u16;
}
}
#[derive(Copy, Clone)]
struct U32X4([u32; 4]);
impl U32X4 {
fn from(bytes: &[u8]) -> Self {
U32X4([
u32::from(bytes[0]),
u32::from(bytes[1]),
u32::from(bytes[2]),
u32::from(bytes[3]),
])
}
}
impl AddAssign<Self> for U32X4 {
fn add_assign(&mut self, other: Self) {
for (s, o) in self.0.iter_mut().zip(other.0.iter()) {
*s += o;
}
}
}
impl RemAssign<u32> for U32X4 {
fn rem_assign(&mut self, quotient: u32) {
for s in self.0.iter_mut() {
*s %= quotient;
}
}
}
impl MulAssign<u32> for U32X4 {
fn mul_assign(&mut self, rhs: u32) {
for s in self.0.iter_mut() {
*s *= rhs;
}
}
}