acme-memorandom: Memoized random number generation
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A library for generating random numbers in a memoized manner. Implemented as
a lazy table indexed by serialized StdGen. Monomorphism is used to
facilitate memoization, users should adapt their design to work with random
Int values only.
In a benchmark, the initial generation of 100000 random Ints took 10.30
seconds and consumed 2.5 gigabytes of memory. Generating the 100000 Ints
again from the same seed only took 2.06 seconds, a 5-fold speedup thanks to
memoization!
Incidentally, generating the 100000 Ints with the non-memoized function
took 0.12 seconds, but that of course lacks all the benefits of memoization.
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Properties
| Versions | 0.0.1, 0.0.2, 0.0.3, 0.0.3 |
|---|---|
| Change log | ChangeLog.md |
| Dependencies | base (>=4 && <5), MemoTrie (>=0.6 && <0.7), random (>=1 && <2) [details] |
| License | MIT |
| Copyright | Copyright © 2015 Johan Kiviniemi |
| Author | Johan Kiviniemi <devel@johan.kiviniemi.name> |
| Maintainer | Johan Kiviniemi <devel@johan.kiviniemi.name> |
| Category | ACME |
| Home page | https://github.com/ion1/acme-memorandom |
| Bug tracker | https://github.com/ion1/acme-memorandom/issues |
| Source repo | head: git clone https://github.com/ion1/acme-memorandom.git |
| Uploaded | by ion at 2015-05-15T23:38:19Z |
Modules
[Index]
- System
- Random
Downloads
- acme-memorandom-0.0.3.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
Maintainer's Corner
Package maintainers
For package maintainers and hackage trustees
Readme for acme-memorandom-0.0.3
[back to package description]acme-memorandom
A library for generating random numbers in a memoized manner. Implemented as a
lazy table indexed by serialized StdGen. Monomorphism is used to
facilitate memoization, users should adapt their design to work with random
Int values only.
In a benchmark, the initial generation of 100000 random Ints took 10.30
seconds and consumed 2.5 gigabytes of memory. Generating the 100000 Ints
again from the same seed only took 2.06 seconds, a 5-fold speedup thanks to
memoization!
Incidentally, generating the 100000 Ints with the non-memoized function took
0.12 seconds, but that of course lacks all the benefits of memoization.