Development of MC/DC: a performant, scalable, and portable Python-based Monte Carlo neutron transport code
Abstract
We discuss the current development of MC/DC (Monte Carlo Dynamic Code). MC/DC is primarily designed to serve as an exploratory Python-based MC transport code. However, it seeks to offer improved performance, massive scalability, and backend portability by leveraging Python code-generation libraries and implementing an innovative abstraction strategy and compilation scheme. Here, we verify MC/DC capabilities and perform an initial performance assessment. We found that MC/DC can run hundreds of times faster than its pure Python mode and about 2.5 times slower, but with comparable parallel scaling, than the high-performance MC code Shift for simple problems. Finally, to further exercise MC/DC's time-dependent MC transport capabilities, we propose a challenge problem based on the C5G7-TD benchmark model.
Cite
@article{arxiv.2305.07636,
title = {Development of MC/DC: a performant, scalable, and portable Python-based Monte Carlo neutron transport code},
author = {Ilham Variansyah and J. P. Morgan and Jordan Northrop and Kyle E. Niemeyer and Ryan G. McClarren},
journal= {arXiv preprint arXiv:2305.07636},
year = {2023}
}
Comments
11 pages, 9 figures, M&C 2023 ANS conference