zeroerr::Rng Class Reference

#include <rng.h>

Public Types
using	result_type = uint64_t
	This RNG provides 64bit randomness. More...

Public Member Functions
	Rng (Rng const &)=delete
Rng &	operator= (Rng const &)=delete
	Rng (Rng &&) noexcept=default
Rng &	operator= (Rng &&) noexcept=default
	~Rng () noexcept=default
	Rng ()
	Creates a new Random generator with random seed. More...
	Rng (uint64_t seed) noexcept
	Rng (uint64_t x, uint64_t y) noexcept
	Rng (std::vector< uint64_t > const &data)
Rng	copy () const noexcept
uint64_t	operator() () noexcept
	Produces a 64bit random value. This should be very fast, thus it is marked as inline. In my benchmark, this is ~46 times faster than std::default_random_engine for producing 64bit random values. It seems that the fastest std contender is std::mt19937_64. Still, this RNG is 2-3 times as fast. More...
uint32_t	bounded (uint32_t range) noexcept
double	uniform01 () noexcept
template<typename Container >
void	shuffle (Container &container) noexcept
std::vector< uint64_t >	state () const

Static Public Member Functions
static uint64_t	min ()
static uint64_t	max ()

Detailed Description

An extremely fast random generator. Currently, this implements RomuDuoJr, developed by Mark Overton. Source: http://www.romu-random.org/

RomuDuoJr is extremely fast and provides reasonable good randomness. Not enough for large jobs, but definitely good enough for a benchmarking framework.

• Estimated capacity: bytes
• Register pressure: 4
• State size: 128 bits

This random generator is a drop-in replacement for the generators supplied by <random>. It is not cryptographically secure. It's intended purpose is to be very fast so that benchmarks that make use of randomness are not distorted too much by the random generator.

Rng also provides a few non-standard helpers, optimized for speed.

Member Typedef Documentation

result_type

using zeroerr::Rng::result_type = uint64_t

This RNG provides 64bit randomness.

Constructor & Destructor Documentation

Rng() [1/6]

zeroerr::Rng::Rng ( Rng const &  )

delete

As a safety precausion, we don't allow copying. Copying a PRNG would mean you would have two random generators that produce the same sequence, which is generally not what one wants. Instead create a new rng with the default constructor Rng(), which is automatically seeded from std::random_device. If you really need a copy, use copy().

Rng() [2/6]

zeroerr::Rng::Rng ( Rng &&  )

defaultnoexcept

~Rng()

zeroerr::Rng::~Rng ( )

defaultnoexcept

Rng() [3/6]

zeroerr::Rng::Rng

(

)

Creates a new Random generator with random seed.

Instead of a default seed (as the random generators from the STD), this properly seeds the random generator from std::random_device. It guarantees correct seeding. Note that seeding can be relatively slow, depending on the source of randomness used. So it is best to create a Rng once and use it for all your randomness purposes.

Rng() [4/6]

zeroerr::Rng::Rng ( uint64_t  seed )

explicitnoexcept

Creates a new Rng that is seeded with a specific seed. Each Rng created from the same seed will produce the same randomness sequence. This can be useful for deterministic behavior.

embed:rst
.. note::
   The random algorithm might change between nanobench releases. Whenever a faster and/or
better random generator becomes available, I will switch the implementation.

As per the Romu paper, this seeds the Rng with splitMix64 algorithm and performs 10 initial rounds for further mixing up of the internal state.

Parameters

seed	The 64bit seed. All values are allowed, even 0.

Rng() [5/6]

zeroerr::Rng::Rng ( uint64_t  x, uint64_t  y  )

noexcept

Rng() [6/6]

zeroerr::Rng::Rng

(

std::vector< uint64_t > const &

data

)

Member Function Documentation

bounded()

uint32_t zeroerr::Rng::bounded ( uint32_t  range )

inlinenoexcept

Generates a random number between 0 and range (excluding range).

The algorithm only produces 32bit numbers, and is slightly biased. The effect is quite small unless your range is close to the maximum value of an integer. It is possible to correct the bias with rejection sampling (see here, but this is most likely irrelevant in practices for the purposes of this Rng.

See Daniel Lemire's blog post A fast alternative to the modulo reduction

Parameters

range

Upper exclusive range. E.g a value of 3 will generate random numbers 0, 1, 2.

Returns

uint32_t Generated random values in range [0, range).

copy()

Rng zeroerr::Rng::copy ( ) const

noexcept

Creates a copy of the Rng, thus the copy provides exactly the same random sequence as the original.

max()

uint64_t zeroerr::Rng::max ( )

static

min()

uint64_t zeroerr::Rng::min ( )

static

operator()()

uint64_t zeroerr::Rng::operator() ( )

inlinenoexcept

Produces a 64bit random value. This should be very fast, thus it is marked as inline. In my benchmark, this is ~46 times faster than std::default_random_engine for producing 64bit random values. It seems that the fastest std contender is std::mt19937_64. Still, this RNG is 2-3 times as fast.

Returns

uint64_t The next 64 bit random value.

operator=() [1/2]

Rng& zeroerr::Rng::operator= ( Rng &&  )

defaultnoexcept

operator=() [2/2]

Rng& zeroerr::Rng::operator= ( Rng const &  )

delete

Same as Rng(Rng const&), we don't allow assignment. If you need a new Rng create one with the default constructor Rng().

shuffle()

template<typename Container >

void zeroerr::Rng::shuffle ( Container &  container )

inlinenoexcept

Shuffles all entries in the given container. Although this has a slight bias due to the implementation of bounded(), this is preferable to std::shuffle because it is over 5 times faster. See Daniel Lemire's blog post Fast random shuffling.

Parameters

container

The whole container will be shuffled.

state()

std::vector< uint64_t > zeroerr::Rng::state

(

)

const

Extracts the full state of the generator, e.g. for serialization. For this RNG this is just 2 values, but to stay API compatible with future implementations that potentially use more state, we use a vector.

Returns

Vector containing the full state:

uniform01()

double zeroerr::Rng::uniform01 ( )

inlinenoexcept

Provides a random uniform double value between 0 and 1. This uses the method described in Generating uniform doubles in the unit interval, and is extremely fast.

Returns

double Uniformly distributed double value in range [0,1], excluding 1.

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The documentation for this class was generated from the following files:

• include/zeroerr/internal/rng.h
• src/rng.cpp