Yazid, M. S. and Lemaire, M. and Mohd. Sies, M. and Lee, D. (2019) Performance analysis of random sampling algorithms on GNU octave. In: International Nuclear Science, Technology and Engineering Conference 2018, iNuSTEC 2018, 23-25 Nov 2018, Universiti Teknologi Malaysia (UTM) Skudai, Johor, Malaysia.
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Official URL: https://dx.doi.org/10.1088/1757-899X/555/1/012003
Abstract
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 [1]. 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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | inverse transforms, learning algorithms, Monte Carlo methods |
| Subjects: | T Technology > TP Chemical technology |
| Divisions: | Chemical and Energy Engineering |
| ID Code: | 89895 |
| Deposited By: | Narimah Nawil |
| Deposited On: | 04 Mar 2021 02:34 |
| Last Modified: | 04 Mar 2021 02:34 |
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