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 and competitive with or faster than other modern high-speed PRNGs like
wyrandandxoroshiro128++. - 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_stdcompatible and implements the standardRngCoreandSeedableRngtraits fromrand_corefor easy use.
Rust Installation
Add biski64 to your Cargo.toml dependencies:
[]
= "0.1.1"
Basic Usage
use rand_core::{RngCore, SeedableRng};
// Create a new generator from a simple 64-bit seed.
let mut rng = Biski64Rng::seed_from_u64(42);
// Generate a random u64 number.
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
wyrand 0.428 ns/call
xoroshiro128++ 0.934 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_rotandoutputfor each stream as normal. - Assign a unique starting value to the
fast_loopcounter 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).
Reduced State Performance
For testing, the mixer core of biski64 has been reduced to 64bits total state (without the Weyl sequence). This reduced test version passes 16TB of PractRand.
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 a for reduced state demonstration only. Use the above full biski64() implementations 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.