Abstract
We compare GPGPU implementations of two popular models of crowd dynamics. Specifically, we consider a continuous social force model, based on differential equations (molecular dynamics) and a discrete social distances model based on non-homogeneous cellular automata. For comparative purposes both models have been implemented in two versions: on the one hand using GPGPU technology, on the other hand using CPU only. We compare some significant characteristics of each model, for example: performance, memory consumption and issues of visualization. We also propose and test some possibilities for tuning the proposed algorithms for efficient GPU computations.
Keywords
Cite this article
@article{cai-2287,
author = {Jarosław Wąs and Hubert Mróz and Paweł Topa},
title = {GPGPU Computing for Microscopic Simulations of Crowd Dynamics},
journal = {Computing and Informatics},
volume = {34},
number = {6},
pages = {1418--1434},
year = {2015},
issn = {1335-9150},
url = {https://cai.type.sk/content/2015/6/gpgpu-computing-for-microscopic-simulations-of-crowd-dynamics/}
}
TY - JOUR AU - Jarosław Wąs AU - Hubert Mróz AU - Paweł Topa TI - GPGPU Computing for Microscopic Simulations of Crowd Dynamics JO - Computing and Informatics VL - 34 IS - 6 SP - 1418 EP - 1434 PY - 2015 SN - 1335-9150 UR - https://cai.type.sk/content/2015/6/gpgpu-computing-for-microscopic-simulations-of-crowd-dynamics/ KW - Crowd simulation KW - social force KW - social distances KW - cellular automata KW - using GPU in simulation ER -
Wąs, J., Mróz, H., & Topa, P. (2015). GPGPU Computing for Microscopic Simulations of Crowd Dynamics. Computing and Informatics, 34(6), 1418–1434. https://cai.type.sk/content/2015/6/gpgpu-computing-for-microscopic-simulations-of-crowd-dynamics/