Miscellaneaous utility classes. * *
Warning: before release 2.6.3, the {@code split()} method of all generators * would not alter the state of the caller, and it would return instances initialized in the same * way if called multiple times. This was a major mistake in the implementation and it has been fixed, * but as a consequence the output of the caller after a call to {@code split()} is * now different, and the result of {@code split()} is initialized in a different way. * *
We provide a number of fast, high-quality PRNGs with different features. You can get detailed * information about the generators at our PRNG page, together * with a reasoned guide to the choice of the generator that's right for you. * *
A table summarizing timings is provided below. The timings were measured on an * Intel® Core™ i7-8700B CPU @3.20GHz using * JMH microbenchmarks. The JMH timings were decreased by 1ns, as * using the low-level {@code perfasm} profiler the JMH overhead was estimated at ≈1ns per call. * *
| * | {@link java.util.Random Random} * | {@link java.util.concurrent.ThreadLocalRandom ThreadLocalRandom} * | {@link java.util.SplittableRandom SplittableRandom} * | {@link it.unimi.dsi.util.SplitMix64RandomGenerator SplitMix64} * | {@link it.unimi.dsi.util.XoRoShiRo128PlusPlusRandom xoroshiro128++}
* | {@link it.unimi.dsi.util.XoRoShiRo128StarStarRandom xoroshiro128**}
* | {@link it.unimi.dsi.util.XoRoShiRo128PlusRandom xoroshiro128+}
* | {@link it.unimi.dsi.util.XoShiRo256PlusPlusRandom xoshiro256++}
* | {@link it.unimi.dsi.util.XoShiRo256StarStarRandom xoshiro256**}
* | {@link it.unimi.dsi.util.XoShiRo256PlusRandom xoshiro256+}
* | {@link it.unimi.dsi.util.XorShift1024StarPhiRandom xorshift1024*φ}
*
* |
|---|---|---|---|---|---|---|---|---|---|---|---|
| nextLong() | 14.419 | 1.252 | 1.283 | 1.241 | 1.428 | 1.574 | 1.295 | 1.738 | 1.884 | 1.653 | 1.901 * |
| nextInt(100000) | 6.715 | 2.045 | 2.499 | 2.543 | 2.336 | 2.594 | 1.202 | 2.607 | 2.954 | 2.367 | 3.119 * |
| nextDouble() | 14.458 | 1.876 | 2.161 | 2.176 | 1.918 | 2.219 | 1.853 | 2.304 | 2.503 | 2.112 | 2.755 * |
Note that generators that are extremely fast in C, such as xoshiro256+, do not perform particularly well in Java, most likely
* because of the cost of accessing variables, which rises as the size of the state space grows. Indeed,
* smaller-state generators are faster. Moreover, generators based on the ++
* scrambler are slightly faster than those based on the ** scrambler, contrarily to what happens in C.
*
*
For each generator, we provide a version that extends {@link java.util.Random}, overriding (as usual) the {@link java.util.Random#next(int) next(int)} method. Nonetheless, * since the generators are all inherently 64-bit also {@link java.util.Random#nextInt() nextInt()}, {@link java.util.Random#nextFloat() nextFloat()}, * {@link java.util.Random#nextLong() nextLong()}, {@link java.util.Random#nextDouble() nextDouble()}, {@link java.util.Random#nextBoolean() nextBoolean()} * and {@link java.util.Random#nextBytes(byte[]) nextBytes(byte[])} have been overridden for speed (preserving, of course, {@link java.util.Random}'s semantics). * *
If you do not need an instance of {@link java.util.Random}, or if you need a {@link org.apache.commons.math3.random.RandomGenerator} to use * with Commons Math, there is for each generator a corresponding {@link org.apache.commons.math3.random.RandomGenerator RandomGenerator} * implementation, which indeed we suggest to use in general if you do not need a generator implementing {@link java.util.Random}. */ package it.unimi.dsi.util;