The chemical-inspired programming approach is an emerging paradigm for defining the behavior of densely distributed and context-aware devices (e.g., in ecosystems of displays tailored to crowd steering, or to obtain profile-based coordinated visualization). Typically, the evolution of such systems cannot be easily predicted, thus making of paramount importance the availability of techniques and tools supporting prior-to-deployment analysis. Exact analysis techniques do not scale well when the complexity of systems grows: as a consequence, approximated techniques based on simulation assumed a relevant role. This work presents a new simulation-based distributed analysis tool addressing the statistical analysis of such a kind of systems. The tool has been obtained by chaining two existing tools: MultiVeSta and Alchemist. The former is a recently proposed lightweight tool which allows to enrich existing discrete event simulators with automated and distributed statistical analysis capabilities, while the latter is an efficient simulator for chemical-inspired computational systems. The tool is validated against a crowd steering scenario, and insights on the performance are provided by discussing how the analysis tasks scale on a multi-core architecture.

Distributed statistical analysis of complex systems modeled through a chemical metaphor / Danilo Pianini; Stefano Sebastio; Andrea Vandin. - ELETTRONICO. - (2014), pp. 6903715.416-6903715.423. (Intervento presentato al convegno 2014 International Conference on High Performance Computing and Simulation, HPCS 2014 tenutosi a Bologna nel 2014) [10.1109/HPCSim.2014.6903715].

Distributed statistical analysis of complex systems modeled through a chemical metaphor

PIANINI, DANILO;
2014

Abstract

The chemical-inspired programming approach is an emerging paradigm for defining the behavior of densely distributed and context-aware devices (e.g., in ecosystems of displays tailored to crowd steering, or to obtain profile-based coordinated visualization). Typically, the evolution of such systems cannot be easily predicted, thus making of paramount importance the availability of techniques and tools supporting prior-to-deployment analysis. Exact analysis techniques do not scale well when the complexity of systems grows: as a consequence, approximated techniques based on simulation assumed a relevant role. This work presents a new simulation-based distributed analysis tool addressing the statistical analysis of such a kind of systems. The tool has been obtained by chaining two existing tools: MultiVeSta and Alchemist. The former is a recently proposed lightweight tool which allows to enrich existing discrete event simulators with automated and distributed statistical analysis capabilities, while the latter is an efficient simulator for chemical-inspired computational systems. The tool is validated against a crowd steering scenario, and insights on the performance are provided by discussing how the analysis tasks scale on a multi-core architecture.
2014
Proceedings of the 2014 International Conference on High Performance Computing and Simulation, HPCS 2014
416
423
Distributed statistical analysis of complex systems modeled through a chemical metaphor / Danilo Pianini; Stefano Sebastio; Andrea Vandin. - ELETTRONICO. - (2014), pp. 6903715.416-6903715.423. (Intervento presentato al convegno 2014 International Conference on High Performance Computing and Simulation, HPCS 2014 tenutosi a Bologna nel 2014) [10.1109/HPCSim.2014.6903715].
Danilo Pianini; Stefano Sebastio; Andrea Vandin
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/410572
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