Optimizing the use of the C++11 random generator
c++, c++11, optimization, random
Solution
There is always a trade-off between the efficiency, i.e. speed and size (number of bytes of the state), on the one hand and "randomness" of any RNG on the other. The Mersenne twister has quite good randomness (provided you use a high-entropy seed, such as provided by `std::random_device`), but slow and has large state. `std::minstd_rand` or `std::knuth_b` (linear congruential) are faster and `ranlux48` (Fibbonacci) yet faster, but are less random (pass fewer test for randomness, i.e. have some non-random spectral properties). Just experiment and test if you're happy with the randomness provided (i.e. have no unsuspected correlations in the random data).
edit: 1 All these RNG are not truly random, of course, and are also not random enough for cryptography. If you need that, use `std::random_device`, but don't complain about speed. 2 In parallel (which you should consider), use `thread_local` RNGs, each initialised with another seed.
Problem
I'm coding a physics simulation heavily using random numbers, I just profiled my code for the first time so I may be in wrong in reading the output but I see this line coming first: ``` % cumulative self self total time seconds seconds calls ms/call ms/call name 90.09 21.88 21.88 265536 0.08 0.08 std::mersenne_twister_engine<unsigned long, 32ul, 624ul, 397ul, 31ul, 2567483615ul, 11ul, 4294967295ul, 7ul, 2636928640ul, 15ul, 4022730752ul, 18ul, 1812433253ul>::operator()() ``` It seems to mean that generating number generator takes 90% of the time. I had already written a previous post asking if not constructing the random probability distributions at each loop could save me time but after trying and timing it didn't help (Is defining a probability distribution costly? ). Are there common options for optimizing random number generation? Thank you in advance, my simulations (in its current state) runs for days so reducing on 90% of this computation time would be a significant progress.