pcg-random: Haskell bindings to the PCG random number generator.

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PCG is a family of simple fast space-efficient statistically good algorithms for random number generation. Unlike many general-purpose RNGs, they are also hard to predict.

This library implements bindings to the standard C implementation. This includes the standard, unique, fast and single variants in the pcg family. There is a pure implementation that can be used as a generator with the random package as well as a faster primitive api that includes functions for generating common types.

The generators in this module are suitable for use in parallel but make sure threads don't share the same generator or things will go horribly wrong.


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Versions [RSS] 0.1.0.0, 0.1.0.1, 0.1.1.0, 0.1.2.0, 0.1.3.0, 0.1.3.1, 0.1.3.2, 0.1.3.3, 0.1.3.4, 0.1.3.5, 0.1.3.6, 0.1.3.7, 0.1.4.0
Change log CHANGELOG.md
Dependencies base (>=4.3 && <5), bytestring, entropy, primitive (>=0.7 && <0.10), random (>=1.2 && <2.0) [details]
License BSD-3-Clause
Copyright (c) 2014-2015. Christopher Chalmers <c.chalmers@me.com>
Author Christopher Chalmers
Maintainer c.chalmers@me.com
Revised Revision 1 made by cchalmers at 2024-02-01T12:05:54Z
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Home page http://github.com/cchalmers/pcg-random
Bug tracker http://github.com/cchalmers/pcg-random/issues
Source repo head: git clone git://github.com/cchalmers/pcg-random.git
Uploaded by cchalmers at 2023-04-30T15:09:10Z
Distributions Arch:0.1.4.0, LTSHaskell:0.1.4.0, NixOS:0.1.4.0, Stackage:0.1.4.0
Reverse Dependencies 3 direct, 13 indirect [details]
Downloads 11378 total (98 in the last 30 days)
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Readme for pcg-random-0.1.4.0

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pcg-random

Build Status Hackage

Haskell bindings to the PCG random number generator http://www.pcg-random.org.

PCG is a family of simple fast space-efficient statistically good algorithms for random number generation. Unlike many general-purpose RNGs, they are also hard to predict.

Implements the standard multiple stream generator as well as the fast, single and unique variants.

The api is very similar to mwc-random but the pcg generator appears to be slightly faster. There is also a pure interface via the random libray.