Exascale Agent-Based Modelling for Policy Evaluation in Real-Time (ExAMPLER) (Short Paper)

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Titel: Exascale Agent-Based Modelling for Policy Evaluation in Real-Time (ExAMPLER) (Short Paper)

Beteiligte: Heppenstall, Alison [Verfasser:in]; Polhill, J. Gary [Verfasser:in]; Batty, Mike [Verfasser:in]; Hare, Matt [Verfasser:in]; Salt, Doug [Verfasser:in]; Milton, Richard [Verfasser:in]

Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2023

Sprache: Englisch

DOI: https://doi.org/10.4230/LIPIcs.GIScience.2023.38

Schlagwörter: Exascale computing ; Policy evaluation ; Agent-Based Modelling

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Beschreibung: Exascale computing can potentially revolutionise the way in which we design and build agent-based models (ABM) through, for example, enabling scaling up, as well as robust calibration and validation. At present, there is no exascale computing operating with ABM (that we are aware of), but pockets of work using High Performance Computing (HPC). While exascale computing is expected to become more widely available towards the latter half of this decade, the ABM community is largely unaware of the requirements for exascale computing for agent-based modelling to support policy evaluation. This project will engage with the ABM community to understand what computing resources are currently used, what we need (both in terms of hardware and software) and to set out a roadmap by which to make it happen.

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