Journal article
Reprint of: Parallel agent-based modeling of spatial opinion diffusion accelerated using graphics processing units
Ecological modelling, Vol.229, pp.108-118
03/24/2012
DOI: 10.1016/j.ecolmodel.2012.02.003
Abstract
► We parallelize an agent-based opinion model using graphics processing units (GPUs). ► We identify algorithms necessary for the GPU-enabled opinion modeling. ► We examine the capabilities of GPUs in supporting agent-based opinion modeling. ► GPUs accelerate substantially the spatial simulation of opinion exchange.
In this article, we describe a parallel agent-based model of spatial opinion diffusion that is driven by graphics processing units (GPUs). Modeling opinion exchange and diffusion across landscapes often involves the simulation of large numbers of geographically located individual decision-makers and a massive number of individual-level interactions. This simulation requires substantial computational power. GPU-enabled computing resources provide a massively parallel processing platform based on a fine-grained shared memory paradigm. This massively parallel processing platform holds considerable promise for meeting the computing requirement of agent-based models of spatial problems. In this article, we focus on the parallelization of an agent-based spatial opinion model using GPU technologies. We discussed key algorithms designed for parallel agent-based opinion modeling: including domain decomposition and mutual exclusion. Experiments conducted to examine computing performance show that GPUs provide a computationally efficient alternative to traditional parallel computing architectures and substantially accelerate agent-based models of large-scale opinion exchange among individual decision makers.
Details
- Title: Subtitle
- Reprint of: Parallel agent-based modeling of spatial opinion diffusion accelerated using graphics processing units
- Creators
- Wenwu Tang - University of North Carolina at Chapel HillDavid A Bennett - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Ecological modelling, Vol.229, pp.108-118
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.ecolmodel.2012.02.003
- ISSN
- 0304-3800
- eISSN
- 1872-7026
- Language
- English
- Date published
- 03/24/2012
- Academic Unit
- Geographical and Sustainability Sciences
- Record Identifier
- 9984259633602771
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