Permuted congruential generator


A permuted congruential generator is a pseudorandom number generation algorithm developed in 2014 which applies an output permutation function to improve the statistical properties of a modulo-2n linear congruential generator. It achieves excellent statistical performance with small and fast code, and small state size.
A PCG differs from a classical linear congruential generator in three ways:
It is the variable rotation which eliminates the problem of a short period in the low-order bits that power-of-2 LCGs suffer from.

Variants

The PCG family includes a number of variants. The core LCG is defined for widths from 8 to 128 bits, although only 64 and 128 bits are recommended for practical use; smaller sizes are for statistical tests of the technique.
The additive constant in the LCG can be varied to produce different streams. The constant is an arbitrary odd integer, so it does not need to be stored explicitly; the address of the state variable itself can be used.
There are several different output transformations defined. All perform well, but some have a larger margin than others. They are built from the following components:
These are combined into the following recommended output transformations, illustrated here in their most common sizes:
Each step of these output transformations is either invertible or a truncation, so their composition maps the same fixed number of input states to each output value. This preserves the equidistribution of the underlying LCG.
Finally, if a cycle length longer than 2128 is required, the generator can be extended with an array of sub-generators. One is chosen to be added to the main generator's output, and every time the main generator's state reaches zero, the sub-generators are cycled in a pattern which provides a period exponential in the total state size.

Example code

The generator recommended for most users is PCG-XSH-RR with 64-bit state and 32-bit output. It can be implemented as:

  1. include
static uint64_t state = 0x4d595df4d0f33173; // Or something seed-dependent
static uint64_t const multiplier = 6364136223846793005u;
static uint64_t const increment = 1442695040888963407u; // Or an arbitrary odd constant
static uint32_t rotr32
uint32_t pcg32
void pcg32_init

The generator applies the output transformation to the initial state rather than the final state in order to increase the available instruction-level parallelism to maximize performance on modern superscalar processors.
A slightly faster version eliminates the increment, reducing the LCG to a multiplicative generator with a period of only 262, and uses the weaker XSH-RS output function:

static uint64_t mcg_state = 0xcafef00dd15ea5e5u; // Must be odd
uint32_t pcg32_fast
void pcg32_fast_init

The time saving is minimal, as the most expensive operation remains, so the normal version is preferred except in extremis. Still, this faster version also passes statistical tests.
When executing on a 32-bit processor, the 64×64-bit multiply must be implemented using three 32×32→64-bit multiply operations. To reduce that to two, there are 32-bit multipliers which perform almost as well as the 64-bit one, such as 0xf13283ad, or 0xf2fc5985.

Comparison with other pseudorandom number generators

PCG was developed by applying TestU01 to reduced-size variants, and determining the minimum number of internal state bits required to pass BigCrush. BigCrush examines enough data to detect a period of 235, so even an ideal generator requires 36 bits of state to pass it. Some very poor generators can pass if given a large enough state; passing despite a small state is a measure of an algorithm's quality, and shows how large a safety margin exists between that lower limit and the state size used in practical applications.
PCG-RXS-M-XS passes BigCrush with 36 bits of state, PCG-XSH-RR requires 39, and PCG-XSH-RS requires 49 bits of state. For comparison, xorshift*, one of the best of the alternatives, requires 40 bits of state, and Mersenne twister fails despite 19937 bits of state.