I recently added some functionality for random number generation to my modules, which led me on a digression about rand(). This is a short look at some modules for getting random floating point values. A later one will look at random ints and bytes.

Modules for rand() Module

Algorithm Stat

Quality Interval Bits in

output Auto

Seed Predictable Speed CORE::rand

drand48 Bad [0,1) 48 OK Yes 29000 k/s Math::Random::MTwist

MT XS OK [0,1) 53 OK Yes 14000 k/s ntheory

ChaCha20 XS Good [0,1) 53-113 Full No 12000 k/s Math::Prime::Util::GMP

ISAAC XS Good [0,1) 53-64 Good No 14000 k/s Crypt::PRNG

Fortuna XS Good [0,1) 53 Good No 700 k/s Math::Random::MT::Auto

MT XS OK [0,1) 52 Full Yes 5000 k/s Math::Random::MT

MT XS OK [0,1) 32 rand() Yes 2200 k/s Math::Random::Secure

Math::Random::ISAAC Good [0,1) 32 Full No 460 k/s Math::Random::ISAAC

ISAAC XS or PP Good [0,1] 32 None No 5700 k/s

480 k/s Math::Random::Xorshift

Xorshift XS OK [0,1] 32 Time Yes 16000 k/s

Some things we generally want from our random number generators:

Statistically random. Any good CSPRNG will qualify, as will a much faster modern PRNG such as PCG or Xoroshiro128+. The Mersenne Twister is quite good though inferior to the newer choices in a few ways. Xorshift has been found to not be very good but the latest in its family, Xoroshiro128+ is considered excellent. drand48, used by Perl for CORE::rand since 5.19.4, has numerous issues. It is, however, better than the crap-shoot we had in older Perls. Both are listed as having "serious defects" in Jones' guide.

Any good CSPRNG will qualify, as will a much faster modern PRNG such as PCG or Xoroshiro128+. The Mersenne Twister is quite good though inferior to the newer choices in a few ways. Xorshift has been found to not be very good but the latest in its family, Xoroshiro128+ is considered excellent. drand48, used by Perl for CORE::rand since 5.19.4, has numerous issues. It is, however, better than the crap-shoot we had in older Perls. Both are listed as having "serious defects" in Jones' guide. Consistent semantics. rand() returns a uniform floating point number in the half-open interval [0,1). This means we can get 0 but will not every get a 1. If given an argument, then our range goes up to but not including it -- we will get a random representable real from 0 up to but not including the number. This makes things like int(rand(6)) return 0-5 and not occasionally give 6. This also lets us combine adjacent intervals knowing there is no overlap. Two of the modules get this wrong. This has nothing to do with the underlying generator, but with the method chosen to create the return value.

returns a uniform floating point number in the half-open interval [0,1). This means we can get 0 but will not every get a 1. If given an argument, then our range goes up to but not including it -- we will get a random representable real from 0 up to but not including the number. This makes things like return 0-5 and not occasionally give 6. This also lets us combine adjacent intervals knowing there is no overlap. Two of the modules get this wrong. This has nothing to do with the underlying generator, but with the method chosen to create the return value. Quality outputs. An NV in Perl is, by default, a double which can store up to 53 bits in the range [0,1). Some modules only fill the result with 32 bits. While this is fine for rolling dice, it won't give good results in some other scenarios. A Perl build with long double support may have 64 bits of mantissa, and with Quadmath support in 5.22 and later we get a full 113 bits to fill. I decided in my module that the best solution was to fill up the NV, giving them the maximum number of bits. It's no extra work for double and most long double builds. It is a little slower for quadmath, but clearly the customer wants lots of precision so we should honor that. I think anything less than 52 bits is substandard.

An NV in Perl is, by default, a double which can store up to 53 bits in the range [0,1). Some modules only fill the result with 32 bits. While this is fine for rolling dice, it won't give good results in some other scenarios. A Perl build with long double support may have 64 bits of mantissa, and with Quadmath support in 5.22 and later we get a full 113 bits to fill. I decided in my module that the best solution was to fill up the NV, giving them the maximum number of bits. It's no extra work for double and most long double builds. It is a little slower for quadmath, but clearly the customer wants lots of precision so we should honor that. I think anything less than 52 bits is substandard. Good seeding available. Some modules strive to seed with an O/S entropy source including Windows and other fallbacks if /dev/urandom isn't available. Perl's internal seed function tries to use /dev/urandom as well as a bit of random process state. Its main issue is that it only uses 32 bits. A couple modules use the current time, which is generally not a good method. Math::Random::ISAAC punts the problem to the caller on the theory that no seeding is better than bad seeding, so modules using it need a seeding layer. There are some subtleties in seeding ISAAC that some ignore.

Some modules strive to seed with an O/S entropy source including Windows and other fallbacks if /dev/urandom isn't available. Perl's internal seed function tries to use /dev/urandom as well as a bit of random process state. Its main issue is that it only uses 32 bits. A couple modules use the current time, which is generally not a good method. Math::Random::ISAAC punts the problem to the caller on the theory that no seeding is better than bad seeding, so modules using it need a seeding layer. There are some subtleties in seeding ISAAC that some ignore. Repeatable. For testing or simulations we need to be able to repeat the result, therefore we have to be able to manually seed. All the modules except Crypt::PRNG support this. For true cryptographic use we really ought to have a forced-system-entropy-seed mode plus periodic reseeding. Crypt::PRNG operates in this way with no ability for user seeding.

For testing or simulations we need to be able to repeat the result, therefore we have to be able to manually seed. All the modules except Crypt::PRNG support this. For true cryptographic use we really ought to have a forced-system-entropy-seed mode plus periodic reseeding. Crypt::PRNG operates in this way with no ability for user seeding. Unpredictibility. For many uses, such as simulations, this isn't necessary at all. For others it is absolutely critical (breaking online Poker in 1999). This is one of the things that separates CSPRNGs from their lesser (but faster) brethren. It is analagous to using a cryptographic hash (e.g. SHA2) vs. generic hash (e.g. SipHash). The former has stronger guarantees but is often an order of magnitude or more slower. For drand48 or Xorshift, after seeing a single output we know every number that will come out in the future as well as all the previous outputs. With Mersenne Twister it takes 624 results. Methods like PCG and Xoroshiro128+ are much harder to predict though it is not impossible. This feature is a CSPRNG requirement so ISAAC, Salsa20, ChaCha20, and Fortuna completely meet it.

For many uses, such as simulations, this isn't necessary at all. For others it is absolutely critical (breaking online Poker in 1999). This is one of the things that separates CSPRNGs from their lesser (but faster) brethren. It is analagous to using a cryptographic hash (e.g. SHA2) vs. generic hash (e.g. SipHash). The former has stronger guarantees but is often an order of magnitude or more slower. For drand48 or Xorshift, after seeing a single output we know every number that will come out in the future as well as all the previous outputs. With Mersenne Twister it takes 624 results. Methods like PCG and Xoroshiro128+ are much harder to predict though it is not impossible. This feature is a CSPRNG requirement so ISAAC, Salsa20, ChaCha20, and Fortuna completely meet it. Performant. All other things being equal, we'd like it to be fast. A vast amount of time can be spent in the Perl / Module interface, making some of the solutions much slower than the underlying algorithm requires. Even when the interface is well optimized, it masks a lot of the difference, allowing algorithms like ChaCha20 and ISAAC to have not-dissimilar speeds from some fast regular PRNGs and substantially outperform much faster underlying algorithms in some modules. With a bulk interface such as random_bytes() things look slightly different. Note that the worst performing solution is still 100,000 calls per second, so this may be moot for your application if you just need a few numbers.



CORE::rand. Very fast. Separate context for each thread. 32-bit seed, 48-bit state. Very poor quality -- for example the 48th bit will always alternate 1,0,1,0,1,0,... while the 47th goes 0,0,1,1,0,0,1,1,... etc. The bottom bits are not at all random, which is a fundamental property of the type of generator using a non-prime modulus (2^48 in this case). It would be very interesting to see some alternatives (e.g. PCG and Xoroshiro128+) in the Perl core, similar to what we do with hash functions.

Math::Random::MTwist. Excellent alternative to core. It's fast and good quality. Random quality is what one would expect from Mersenne Twister. Lots of options. Threading should be done with OO interface.

ntheory. My module, which I added a ChaCha20 CSPRNG to. It was originally intended for speeding up large random prime construction vs. using Bytes::Random::Secure, but it is useful for a standard rand interface as well (srand, rand, irand, irand64, random_bytes, plus some more). ChaCha20 is the CSPRNG which is being used in new arc4random functions in *BSD, is the chosen method for /dev/urandom in Linux 4.18, is used in some new TLS methods, and is increasingly popular as a CSPRNG or stream cipher. The standard implementation isn't as fast as the ISAAC core, but there are AVX2 implementations that are a lot faster. Performance here doesn't suffer much vs. other alternatives, and it's in the top performance tier (albeit at the bottom of the leaders, but 2x faster than many other modules). Seeds at startup using a number of possible sources, and allows easy reseeding with a decent amount of system entropy. It also contains a full ChaCha20 implementation in Perl, as well as matching XS and Perl implementations of ISAAC, though using ISAAC is a build-time configuration option likely to be removed. Uses a single state and mutex lock for threads, which will be replaced by per-thread state in a later release.

Math::Prime::Util::GMP. Uses ISAAC in XS and runs quite a bit faster than the other ISAAC modules. Seeds at startup using /dev/urandom if possible. It wasn't really intended to be a primary module for this work, but it's an interesting comparison with the other ISAAC modules, especially the performance. No threading support.

Crypt::PRNG. An API for LibTomCrypt and part of the large CryptX package. It has a few choices, with the default being Fortuna -- an entropy pool framework with multiple entropy input streams, using AES in counter mode for the actual stream. Very high quality results, well done interface. The only downside is the slow performance, which is typical of the AES-CTR algorithm (when implemented without specific hardware support).

Math::Random::MT::AutoNot a bad module, but it seems to be superceded by MTwist, in that the latter is over 2x faster and doesn't seem to be missing many (any?) features.

Math::Random::MT. An earlier module than the above. Simpler, slower, and seeds from CORE::rand. Only allows 32-bits of state to be set by the user. Only fills returned doubles with 32-bits.

Math::Random::Secure. Gives a (srand,irand,rand) interface to Math::Random::ISAAC, including proper seeding. Large dependency list. Only fills returned doubles with 32-bits. Very slow, and even slower if Math::Random::ISAAC::XS isn't installed.

Math::Random::ISAAC. The first pure Perl implementation of ISAAC, widely copied or used by other modules. There is also an XS back end. Creates double output for rand() by dividing a random 32-bit int by 2^32-1 which makes the non-standard interval [0,1] and only uses 32-bits. No auto seeding is done.

Math::Random::Xorshift. A thin wrapper around Marsaglia's 2003 Xorshift PRNG. As the module author points out, this has some statistical flaws, though the later xorshift* algorithm fixed most of them and xoroshiro128+ is significantly better. Per thread context. Creates double output for rand() by dividing a random 32-bit int by 2^32-1 which makes the non-standard interval [0,1] and only uses 32-bits. Seeds with time. The primary advantage is that it runs faster than the other modules.