pcg-random: Haskell bindings to the PCG random number generator.
PCG is a family of simple fast space-efficient statistically good algorithms for random number generation with better-than-typical cryptographic security.
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), primitive (>=0.4 && <0.6), random (>=1.0 && <2.0), time [details] |
| License | BSD-3-Clause |
| Copyright | (c) 2014. Christopher Chalmers <c.chalmers@me.com> |
| Author | Christopher Chalmers |
| Maintainer | c.chalmers@me.com |
| Category | System |
| 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 2015-02-04T15:07:05Z |
| 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, 15 indirect [details] |
| Downloads | 11665 total (5 in the last 30 days) |
| Rating | (no votes yet) [estimated by Bayesian average] |
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| Status | Docs uploaded by user Build status unknown [no reports yet] |
Readme for pcg-random-0.1.0.1
[back to package description]pcg-random
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 with better-than-typical cryptographic security
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.