PRNGine

PRNGine is a pseudo-random number generator library for sequential and parallel Monte Carlo simulations. All PRNG implementations of this library extends the Java RandomGenerator class, which makes it easily usable in other projects. The PRNGs are not cryptographically strong RNGs.

The following PRNGs are implemented:

• KISS32Random: Implementation of an simple PRNG as proposed in Good Practice in (Pseudo) Random Number Generation for Bioinformatics Applications (JKISS32, page 3) David Jones, UCL Bioinformatics Group.
• KISS64Random: Implementation of an simple PRNG as proposed in Good Practice in (Pseudo) Random Number Generation for Bioinformatics Applications (JKISS64, page 10) David Jones, UCL Bioinformatics Group.
• LCG64ShiftRandom: This class implements a linear congruential PRNG with additional bit-shift transition. It is a port of the trng::lcg64_shift PRNG class of the TRNG library created by Heiko Bauke.
• MT19937_32Random: This is a 32-bit version of Mersenne Twister pseudorandom number generator.
• MT19937_64Random: This is a 64-bit version of Mersenne Twister pseudorandom number generator.
• XOR32ShiftRandom: This generator was discovered and characterized by George Marsaglia [Xorshift RNGs]. In just three XORs and three shifts (generally fast operations) it produces a full period of 2³² - 1 on 32 bits. (The missing value is zero, which perpetuates itself and must be avoided.) High and low bits pass Diehard.
• XOR64ShiftRandom: This generator was discovered and characterized by George Marsaglia [Xorshift RNGs]. In just three XORs and three shifts (generally fast operations) it produces a full period of 2⁶⁴ - 1 on 64 bits. (The missing value is zero, which perpetuates itself and must be avoided.) High and low bits pass Diehard.

NOTE

All implemented random generators are not thread-safe. If they are used in a multi-threaded environment, they must be synchronized externally.

Requirements

• JDK 17: You need Java 17 for building the library.

Building PRNGine

For building the PRNGine library you have to check out the master branch from Github.

$ git clone https://github.com/jenetics/prngine.git

Executing the tests:

$ cd prngine
$ ./gradle test

Building the library:

$ ./gradle jar

Examples

PRNG creation

All random generators can be created with new or via the RandomGenerator.of("<name>") or RandomGeneratorFactory.of("<name>") factory method.

final LCG64ShiftRandom random1 = new LCG64ShiftRandom();
final RandomGenerator random2 = RandomGenerator.of("LCG64ShiftRandom");
final RandomGenerator random3 = RandomGeneratorFactory.of("LCG64ShiftRandom").create();

PRNG seeding

The library also contains methods for creating random seed values, which can be used for initializing the available PRNGs.

// Creating a new 64 bit seed value.
final long seed = Seeds.seed();
final Random ranomd = new LCG64ShiftRandom(seed);

Every random engine has a seedBytes() method, which return the seed byte[] array with the length required by the PRNG.

// This random creation is equivalent to...
final RandomGenerator random1 = new LCG64ShiftRandom();

// ...creating it with the seed bytes of the PRNG. 
final byte[] seed = LCG64ShiftRandom.seedBytes();
final RandomGenerator random2 = new LCG53ShiftRandom(seed);

Test results

Statistical tests (dieharder)

All implemented PRNGs has been tested with the dieharder test suite.

PRNG	Passed	Weak	Failed
KISS32Random	113	1	0
KISS64Random	109	5	0
LCG64ShiftRandom	111	3	0
MT19937_32Random	111	3	0
MT19937_64Random	108	6	0
XOR32ShiftRandom	103	6	5
XOR64ShiftRandom	113	1	0
L64X256MixRandom	111	3	0

Runtime performance tests

The runtime performance of the PRNGs was tested with the JMH testing framework on an Intel Core i7-6700HQ CPU @ 2.60GHz with Java SE Runtime Environment (build 1.8.0_112-b15)—Java HotSpot.

PRNG	10e6 ints/s	10e6 floats/s	F range	10e6 longs/s	10e6 doubles/s
KISS32Random	169	143	126	124	108
KISS64Random	128	124	100	131	120
LCG64ShiftRandom	234	168	19	244	185
MT19937_32Random	164	127	113	92	82
MT19937_64Random	148	120	107	148	120
XOR32ShiftRandom	206	160	144	135	120
XOR64ShiftRandom	189	156	143	207	166
L64X256MixRandom	162	136	121	166	142

License

The library is licensed under the Apache License, Version 2.0.

Copyright 2017-2021 Franz Wilhelmstötter

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Release notes

2.0.0

• Make the random generators work seamlessly with the new Java 17 RandomGenerator API.

1.1.0

Improvements

• #26: Convert Gradle build scripts from Groovy to Kotlin and prepare for Java 11.

1.0.2

Improvements

• #21: Update Gradle version and add CI build for Java 11.

Bugs

• #20: Fix alerts found by LGTM.

1.0.1

Improvements

• #3: Define stable module name. Set the Automatic-Module-Name to io.jenetics.prngine.