Performance analysis of random sampling algorithms on GNU Octave

摘要

This paper presents the performance analysis of two random sampling algorithms, the inverse-transform method and the Vose aliasing method, on GNU Octave. The Monte Carlo code MCS developed by UNIST uses random sampling methods to simulate the physics of neutron and photon transport . The goal is to optimize the sampling time of MCS for cases when the probability density function is a constant function throughout the simulation. For this purpose, the runtime of the inverse-transform method and Vose aliasing method are compared for increasing input size with scripts developed on GNU Octave. To compare the execution time, the initialization and generation time of both methods are determined and discussed.