I'm looking for a performant, reasonably robust RNG using no special hardware. It can use mathematical methods (Mersenne Twister, etc), it can "collect entropy" from the machine, whatever. On Linux/etc we have a `drand48()`

which generates 48 random bits. I'd like a similar function/class for C++ or C# which can generate more than 32 bits of randomness and which low-order bits are equally as random as high-order bits.

It doesn't have to be cryptographically secure but it must not use or be based on the C-language `rand()`

or .NET `System.Random`

.

Any source code, links to source, etc. would be appreciated! Failing that, what TYPE of RNG should I be looking for?

For C++, Boost.Random is probably what you're looking for. It has support for MT (among many other algorithms), and can collect entropy via the

`nondet_random`

class. Check it out! :-)The Gnu Scientific Library (GSL) has a pretty extensive set of RN generators, test harness, etc. If you're on linux, it's probably already available on your system.

Watch out for the Gnu Scientific Library. It's licensed under the GPL rather than LGPL.

As other folks mentioned, the Boost random classes are a good start. Their implementation conforms to the PRNG code slated for TR1:

http://www.boost.org/doc/libs/1_35_0/libs/random/index.html http://www.open-std.org/jtc1/sc22/wg21/docs/papers/2003/n1452.html

If you have a recent version of the G++ compiler, you may find the TR1 libraries already included

C++11 has adopted a robust random number library based on boost.random. You can access a number of random number engines using different algorithms to meet your quality, speed, or size requirements. Quality implementations will even provide access to whatever non-deterministic RNG your platform offers via

`std::random_device`

.In addition there are many adaptors to produce specific distributions, eliminating the need to do such manipulation by hand (something often done incorrectly).

`#include <random>`

`Boost.Random`

is my first choice for RNGhttp://www.boost.org/doc/libs/random