Parallelization strategies for spatial agent-based models
dc.contributor.author | Fachada, Nuno | |
dc.contributor.author | Lopes, Vitor V. | |
dc.contributor.author | Martins, Rui C. | |
dc.contributor.author | Rosa, Agostinho C. | |
dc.date.accessioned | 2020-06-01T10:33:01Z | |
dc.date.available | 2020-06-01T10:33:01Z | |
dc.date.issued | 2017 | |
dc.description | International Journal of Parallel Programming | en |
dc.description.abstract | Agent-based modeling (ABM) is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. Large scale emergent behavior in ABMs is population sensitive. As such, the number of agents in a simulation should be able to reflect the reality of the system being modeled, which can be in the order of millions or billions of individuals in certain domains. A natural solution to reach acceptable scalability in commodity multi-core processors consists of decomposing models such that each component can be independently processed by a different thread in a concurrent manner. In this paper we present a multithreaded Java implementation of the PPHPC ABM, with two goals in mind: (1) compare the performance of this implementation with an existing NetLogo implementation; and, (2) study how different parallelization strategies impact simulation performance on a shared memory architecture. Results show that: (1) model parallelization can yield considerable performance gains; (2) distinct parallelization strategies offer specific trade-offs in terms of performance and simulation reproducibility; and, (3) PPHPC is a valid reference model for comparing distinct implementations or parallelization strategies, from both performance and statistical accuracy perspectives. | en |
dc.format | application/pdf | |
dc.identifier.citation | Fachada, N., Lopes, V. V., Martins, R. C., & Rosa, A. C. (2017). Parallelization strategies for spatial agent-based models. International Journal of Parallel Programming, 45(3), 449-481 | pt |
dc.identifier.issn | 1573-7640 | |
dc.identifier.uri | https://doi.org/10.1007/s10766-015-0399-9 | |
dc.identifier.uri | http://hdl.handle.net/10437/10198 | |
dc.language.iso | eng | pt |
dc.publisher | Springer | en |
dc.rights | openAccess | |
dc.subject | AGENT-BASED MODELING | en |
dc.subject | SHARED MEMORY | en |
dc.subject | MULTITHREADING | en |
dc.subject | MODELAÇÃO BASEADA EM AGENTES | pt |
dc.subject | MEMÓRIA COMPARTILHADA | pt |
dc.subject | MULTISSEGMENTAÇÃO | pt |
dc.title | Parallelization strategies for spatial agent-based models | en |
dc.type | article | en |
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