biski64: Fast and Robust 2^64 Period Pseudo-Random Number Generator

This repository contains biski64, an extremely fast pseudo-random number generator (PRNG) with a guaranteed period of 2^64. It is designed for non-cryptographic applications where speed and statistical quality are important.

The library is available on crates.io and the documentation can be found on docs.rs.

Features

High Performance: Significantly faster than standard library generators modern high-speed PRNGs like xoroshiro128++ and xoshiro256++.
Good Statistical Quality: Has passed PractRand (up to 32TB) with zero anomalies and has shown exceptional results in 100 runs of BigCrush.
Guaranteed 2^64 Period: Incorporates a 64-bit Weyl sequence to ensure a minimum period of 2^64.
Rust Ecosystem Integration: The library is no_std compatible and implements the standard RngCore and SeedableRng traits from rand_core for easy use.

Rust Installation

Add biski64 and rand to your Cargo.toml dependencies:

[dependencies]
biski64 = "0.2.2"
rand = "0.9"

Basic Usage

use rand::{RngCore, SeedableRng};
use biski64::Biski64Rng;

let mut rng = Biski64Rng::seed_from_u64(12345);
let num = rng.next_u64();

Third Party Testing

Christopher Wellons (skeeto) has tested biski64 in his PRNG Shootout and commented in Reddit:

Great stuff! When I plug it into my shootout, it's as fast as dualmix128 (i.e. saturates my benchmark), but with loopmix128's better properties. The 40-byte state is slightly heavy, but not bad at all, and certainly better than the gigantic states of classical PRNGs (Mersenne Twister, Lagged Fibonacci). As far as I can tell, biski64 would be a good PRNG to deploy in real programs.

Performance

Rust Speed:

  biski64            0.366 ns/call
  xoshiro256++       0.659 ns/call
  xoroshiro128++     0.879 ns/call

C Speed:

  biski64            0.418 ns/call
  wyrand             0.449 ns/call
  sfc64              0.451 ns/call
  xoshiro256++       0.593 ns/call
  xoroshiro128++     0.802 ns/call
  PCG128_XSL_RR_64   1.204 ns/call

Rust Algorithm

use std::num::Wrapping;

// In the actual implementation, these are fields of the Biski64Rng struct.
let (mut fast_loop, mut mix, mut last_mix, mut old_rot, mut output) = 
    (Wrapping(0), Wrapping(0), Wrapping(0), Wrapping(0), Wrapping(0));

const GR: Wrapping<u64> = Wrapping(0x9e3779b97f4a7c15);

#[inline(always)]
pub fn next_u64() -> u64 {
    let old_output = output;
    let new_mix = old_rot + output;

    output = GR * mix;
    old_rot = Wrapping(last_mix.0.rotate_left(18));

    last_mix = fast_loop ^ mix;
    mix = new_mix;

    fast_loop += GR;

    old_output.0
}

C Algorithm

// Golden ratio fractional part * 2^64
const uint64_t GR = 0x9e3779b97f4a7c15ULL;

// Helper for rotation
static inline uint64_t rotateLeft(const uint64_t x, int k) {
    return (x << k) | (x >> (64 - k));
}

uint64_t biski64() {
  uint64_t newMix = old_rot + output;

  output = GR * mix;
  old_rot = rotateLeft(last_mix, 18);

  last_mix = fast_loop ^ mix; 
  mix = newMix;

  fast_loop += GR;

  return output;
  }

(Note: See test files for full seeding and usage examples.)

BigCrush

BigCrush was run 100 times on biski64 (as well as on the below mentioned reference PRNGs).

Assuming test failure with a p-value below 0.001 or above 0.999 implies a 0.2% probability of a single test yielding a "false positive" purely by chance with an ideal generator. Running BigCrush 100 times (for a total of 25400 sub-tests), around 50.8 such chance "errors" would be anticipated.

biski64, 47 failed subtests (out of 25400 total)
  2 subtests failed twice

wyrand, 55 failed subtests (out of 25400 total)
  1 subtest failed THREE times
  5 subtests failed twice

sfc64, 70 failed subtests (out of 25400 total)
  1 subtest failed THREE times
  12 subtests failed twice

xoroshiro128++, 54 failed subtests (out of 25400 total)
  1 subtest failed FOUR times
  4 subtests failed twice

xoroshiro256++, 60 failed subtests (out of 25400 total)
  1 subtest failed THREE times
  5 subtests failed twice

pcg128_xsl_rr_64, 47 failed subtests (out of 25400 total)
  1 subtest failed FIVE times
  4 subtests failed twice

(Note: For an ideal random generator, seeing three or more failures for a specific subtest would not be expected.)

Parallel Streams

The Weyl sequence of biski64 is well-suited for parallel applications, and parallel streams can be implemented as follows:

Randomly seed mix, last_mix, old_rot and output for each stream as normal.
Assign a unique starting value to the fast_loop counter for each stream. To ensure maximal separation between sequences, these starting values should be spaced far apart. A simple strategy is to assign the i-th stream's counter as: fast_loop_i = initial_fast_loop_seed + i * GR;

where i is the stream index (0, 1, 2, ...) and GR is the golden ratio constant (0x9e3779b97f4a7c15ULL).

Design

The design process followed modern PRNG principles, focusing on creating a strong core mixer and then combining it with a simple counter to guarantee the period.

Core Mixer: The initial focus was developing a strong mixer, motivated by M.E. O'Neill's challenge in her post, Does It Beat the Minimal Standard. The developed mixer core (with 64-bits of state) passes 16TB of PractRand.
Guaranteed Period: A Weyl sequence was added to provide a guaranteed minimum period of 2^64. Separating the task of period generation from statistical mixing was a deliberate trade-off.
Performance: Finally, additional state variables were introduced to enable instruction-level parallelism for maximum speed.

The reduced state 64-bit core mixer at the heart of the algorithm is as follows:

uint32_t output = GR * mix;
uint32_t old_rot = rotateLeft(last_mix, 11);

last_mix = GR ^ mix;
mix = old_rot + output;

return output;

(Note: This reduced state mixer is for demonstration only. Use the above full implementation to ensure pipelined performance and the minimum period length of 2^64.)

Notes

Created by Daniel Cota and named after his cat Biscuit - a small and fast Egyptian Mau.

biski64 0.2.2