SFMT与Mersenne Twister和Ran2的比较

Question

I am trying to optimise a C-based code used for bioinformatic purposes. It uses Monte Carlo iterations for major part of the calculations. It earlier used ran2() for generating random numbers, which was making it super slow. After thorough research, I found that mersenne twister, and sfmt are more efficient random number generators. However, I tried using them in my code, and they seem to be making not much of a difference in the speed. Given the fact that the program uses generator 10+ times for each iteration, I am not able to figure out why changing the generator is making no difference to the speed.

Could anyone tell me where am I possibly going wrong?

Answer 1

Choosing a random number generator is always a balance between quality (of the numbers they generate) and speed. Linear congruential generators are typically the fastest, but they are not suitable for any serious Monte Carlo work.

From experience I'd say that mersenne twister is just fine --- it's not superslow and you don't have to worry about the quality. As long as the bottleneck is in the generator, I'd say there's not much you can do on a single core.

This being said, here's a comparison of several generators: http://www.boost.org/doc/libs/1_48_0/doc/html/boost_random/performance.html