Large-Scale Parallelization of Human Migration Simulation
Bibliographic Data
| ID | 22108293 |
|---|---|
| Authors | Derek Groen (0000-0001-7463-3765, Brunel University of London), Nikela Papadopoulou (0000-0003-2141-5654, National Technical University of Athens), Petros Anastasiadis (0000-0001-7821-3610, National Technical University of Athens), Marcin Lawenda (0000-0003-4844-3655, Poznan Supercomputing and Networking Center), Lukasz Szustak (0000-0001-7429-6981, Poznan Supercomputing and Networking Center), Sergiy Gogolenko (0000-0003-4957-5377, University of Stuttgart), Hamid Arabnejad (0000-0002-0789-1825, Brunel University of London), Alireza Jahani (0000-0001-9813-352X, Brunel University of London) |
| Year | 2024 |
| Volume | 11 |
| Issue | 2 |
| Pages | 2135-2146 |
| Publication date | 2024-04-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2023.3292932 |
| OpenAlex | W4385516893 |
| Language | EN |
| References cited | 45 |
Forced displacement of people worldwide, for example, due to violent conflicts, is common in the modern world, and today more than 82 million people are forcibly displaced. This puts the problem of migration at the forefront of the most important problems of humanity. The Flee simulation code is an agent-based modeling tool that can forecast population displacements in civil war settings, but performing accurate simulations requires nonnegligible computational capacity. In this article, we present our approach to Flee parallelization for fast execution on multicore platforms, as well as discuss the computational complexity of the algorithm and its implementation. We benchmark parallelized code using supercomputers equipped with AMD EPYC Rome 7742 and Intel Xeon Platinum 8268 processors and investigate its performance across a range of alternative rule sets, different refinements in the spatial representation, and various numbers of agents representing displaced persons. We find that Flee scales excellently to up to 8192 cores for large cases, although very detailed location graphs can impose a large initialization time overhead
Bottleneck · Cartography · Concurrency · Distributed computing · Embedded system · Initialization · Multi-core processor · Parallel computing · Population · Programming language · Xeon · Xeon Phi · Computer Science · Engineering · Evacuation and Crowd Dynamics · Human Mobility and Location-Based Analysis · Multi-Agent Systems and Negotiation
Modelling disease outbreaks in realistic urban social networks
A Stochastic and Flexible Activity Based Model for Large Population. Application to Belgium
Hybrid Agent Modeling in Population Simulation
A Survey of Agent Platforms
Computational Tools in Predicting and Assessing Forced Migration
The Oxford Handbook of Refugee and Forced Migration Studies
| Citation velocity | historical |
|---|---|
| Highly cited | No |