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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Online-Zugang: | https://arxiv.org/abs/2406.14441 |
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| _version_ | 1866912663236247552 |
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| author | Fürst, Steffen Conrad, Tim Jaeger, Carlo Wolf, Sarah |
| author_facet | Fürst, Steffen Conrad, Tim Jaeger, Carlo Wolf, Sarah |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_14441 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Vahana.jl -- A framework (not only) for large-scale agent-based models Fürst, Steffen Conrad, Tim Jaeger, Carlo Wolf, Sarah Multiagent Systems Distributed, Parallel, and Cluster Computing 37E25 D.1.3; I.6.5; J.4 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. |
| title | Vahana.jl -- A framework (not only) for large-scale agent-based models |
| topic | Multiagent Systems Distributed, Parallel, and Cluster Computing 37E25 D.1.3; I.6.5; J.4 |
| url | https://arxiv.org/abs/2406.14441 |