Vahanajl -- A framework (not only) for large-scale agent-based models
<|reference_start|>Vahanajl -- A framework (not only) for large-scale agent-based models: Agent-based models (ABMs) offer a powerful framework for understanding complex systems. However, their computational demands often become a significant barrier as the number of agents and complexity of the simulation increase. Traditional ABM platforms often struggle to fully exploit modern computing resources, hindering the development of large-scale simulations. This paper presents Vahana.jl, a high performance computing open source framework that aims to address these limitations. Building on the formalism of synchronous graph dynamical systems, Vahana.jl is especially well suited for models with a focus on (social) networks. The framework seamlessly supports distribution across multiple compute nodes, enabling simulations that would otherwise be beyond the capabilities of a single machine. Implemented in Julia, Vahana.jl leverages the interactive Read-Eval-Print Loop (REPL) environment, facilitating rapid model development and experimentation.<|reference_end|>
@article{fürst2024vahana.jl,
    title={Vahana.jl -- A framework (not only) for large-scale agent-based models},
    author={Steffen F"urst and Tim Conrad and Carlo Jaeger and Sarah Wolf},
    journal={arXiv preprint arXiv:2406.14441},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.14441},
    primaryClass={cs.MA cs.DC}
}