Flexible Memory Allocation in Kinetic Monte Carlo Simulations

Author

Aaron David Craig, University of Tennessee - KnoxvilleFollow

Date of Award

5-2015

Degree Type

Thesis

Degree Name

Master of Science

Major

Mathematics

Major Professor

Timothy P. Schulze

Committee Members

Charles R. Collins, Steven M. Wise

Abstract

We introduce two new algorithms for Kinetic Monte Carlo simulations: the minimal and flexible allocation algorithms. The theory and computational challenges associated with K.M.C. simulations are briefly discussed. We outline the simple cubic, solid-on-solid model of epitaxial growth and analyze four methods for its simulation: the linear search, standard inverted list, minimal allocation, and flexible allocation algorithms. We then implement these algorithms, analyze their performances, and discuss implications of the results.

Recommended Citation

Craig, Aaron David, "Flexible Memory Allocation in Kinetic Monte Carlo Simulations. " Master's Thesis, University of Tennessee, 2015.
https://trace.tennessee.edu/utk_gradthes/3355