The mwc-random package

[Tags: bsd3, library]

This package contains code for generating high quality random numbers that follow either a uniform or normal distribution. The generated numbers are suitable for use in statistical applications.

The uniform PRNG uses Marsaglia's MWC256 (also known as MWC8222) multiply-with-carry generator, which has a period of 2^8222 and fares well in tests of randomness. It is also extremely fast, between 2 and 3 times faster than the Mersenne Twister.

Compared to the mersenne-random package, this package has a more convenient API, is faster, and supports more statistical distributions.

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Change logNone available
Dependenciesbase (<5), primitive, time, vector (>=0.5) [details]
Copyright2009, 2010 Bryan O'Sullivan
AuthorBryan O'Sullivan <>
MaintainerBryan O'Sullivan <>
CategoryMath, Statistics
Home page
Source repositoryhead: hg clone
UploadedMon Sep 13 04:44:43 UTC 2010 by BryanOSullivan
DistributionsDebian:, Fedora:, FreeBSD:, LTSHaskell:, NixOS:, Stackage:
Downloads61083 total (172 in last 30 days)
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StatusDocs uploaded by user
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Maintainers' corner

For package maintainers and hackage trustees

Readme for mwc-random-

Efficient, general purpose pseudo-random number generation

This package provides the System.Random.MWC module, a Haskell library
for generating high-quality pseudo-random numbers in a space- and
time-efficient way.


This library has been carefully optimised for high performance.  To
obtain the best runtime efficiency, it is imperative to compile
libraries and applications that use this library using a high level of

Suggested GHC options:

  -O -fvia-C -funbox-strict-fields

To illustrate, here are the times (in seconds) to generate and sum 250
million random Word32 values, on a laptop with a 2.4GHz Core2 Duo
P8600 processor, running Fedora 11 and GHC 6.10.3:

  no flags   200+
  -O           1.249
  -O -fvia-C   0.991

As the numbers above suggest, compiling without optimisation will
yield unacceptable performance.

Get involved!

Please feel welcome to contribute new code or bug fixes.  You can
fetch the source repository from here:


Bryan O'Sullivan <>