Testing unrolling optimization technique for quasi random numbers

Quasi Monte Carlo simulations are built on quasi random number generator (QRNG). Even if the use of a QRNG might lead to a faster convergence, for example with Monte Carlo integral computation, most of the simulation time can be taken by the number generation part. This paper present an optimization technique, called “unrolling” applied to QRNG. It consists in the generation and storage of random numbers in a compiled binary object file. After that, the library is used at the execution time by the simulator. We obtained good gains with “Unrolling” technique and QRNG, allowing a minimum gain factor of 4 on different computer architectures compared to the Sobol algorithm.