https://github.com/tokenrove/granderl

Fast-and-loose PRNG NIF
https://github.com/tokenrove/granderl

erlang library nif pcg prng rdrand xorshift

Last synced: 16 days ago
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Fast-and-loose PRNG NIF

• Host: GitHub
• URL: https://github.com/tokenrove/granderl
• Owner: tokenrove
• Created: 2016-01-22T21:12:03.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2023-10-26T15:01:03.000Z (about 1 year ago)
• Last Synced: 2024-09-21T10:15:09.661Z (about 2 months ago)
• Topics: erlang, library, nif, pcg, prng, rdrand, xorshift
• Language: C
• Homepage:
• Size: 788 KB
• Stars: 8
• Watchers: 6
• Forks: 12
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

        
# What is this?

Experiments in fast "random" number generation for Erlang; though they

have the same interface as `rand:uniform/1`, think of them more like

`phash2/2` with a timestamp -- not really random, but fast

(hopefully).

Specifically, some of the PRNGs here use methods that are known to be

biased.  They are not suitably for any application which assumes

uniformity.  They are also not guaranteed to produce uncorrelated

streams when used in parallel.

# Building

Use [rebar3](http://www.rebar3.org/).  To override the default

implementation choice, you can set the `IMPLEMENTATION` environment

variable:

```

$ IMPLEMENTATION=rdrand rebar3 compile

```

# Interface

All functions take an integer between 1 and 232-1, and

return an integer between 1 and the supplied integer, like

`rand:uniform/1`.

## `granderl:`

### `uniform(N :: 1..4294967295) -> 1..4294967295`

# Implementations

## `rdrand`

32-bits of [`RDRAND`](https://en.wikipedia.org/wiki/RdRand).

## `xorshift`

Marsaglia's original

[xorshift](https://en.wikipedia.org/wiki/Xorshift) (with no

multiplies), keeping state in thread-local storage.  Initialized on

first call.

## `pcg32`

[PCG](http://www.pcg-random.org), TLS.

## `msws`

Middle Square Weyl Sequence, keeping state in thread-local storage.

Initialized on first call.

# References

Fog, Agner. ["Pseudo-Random Number Generators for Vector Processors and Multicore Processors."](http://orbit.dtu.dk/ws/files/118886115/Fog_Pseudo_Random_Number_Generators.pdf) Journal of Modern Applied Statistical Methods 14.1 (2015): 308-334.

Marsaglia, George. ["Xorshift RNGs."](http://www.jstatsoft.org/article/view/v008i14) Journal of Statistical Software 8.14 (2003): 1-6.

O'Neill, M.E. ["PCG: A Family of Simple Fast Space-Efficient Statistically Good Algorithms for Random Number Generation"](http://www.pcg-random.org/pdf/toms-oneill-pcg-family-v1.02.pdf).

Widynsky, Bernard. ["Middle Square Weyl Sequence RNG"](https://arxiv.org/pdf/1704.00358.pdf).

# License

Because the pcg32 code is derived from Apache-licensed code (see

c_src/pcg32.c), this package is also

[Apache licensed](http://www.apache.org/licenses/LICENSE-2.0).