WIP - Promoting good modeling practice with a domain-specific language and statistical algorithms designed for parallel computing
Authors: 
Benoît Bayol, Yuting Chen, Charlotte Baey, Gautier Viaud, Paul-Henry CournèdeAuthors Info & Claims
Benoît Bayol, Yuting Chen, Charlotte Baey, Gautier Viaud, Paul-Henry CournèdeAuthors Info & ClaimsPages 143 - 148
Abstract
In this paper we present a platform that mixes a domain-specific language for stochastic discrete dynamical models implemented with LLVM and a C++ multi-threaded library for the simulation, analysis and statistical evaluation of these models. More precisely, the user can easily implement a dynamic model, specifying the state and exogenous variables, parameters, state and observation functions, noises, and then run simple simulations, sensitivity analysis, parameter estimation, data assimilation or uncertainty analysis on computation clusters. We believe that this platform can foster good modeling practices since it simplifies the management of data, models and simulations on clusters and it demonstrates the different steps for a proper model design and evaluation. This platform was initially developed for the plant growth modeling community, for which such methodological tools are deeply needed, since a large variety of models coexist in the literature with generally an absence of benchmarking between the different approaches and insufficient model evaluation. However, the software can be used in any scientific field for which discrete dynamical models are developed.
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- WIP - Promoting good modeling practice with a domain-specific language and statistical algorithms designed for parallel computing
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Published In
April 2015
288 pages
ISBN:9781510801059
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- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- SCS: Society for Modeling and Simulation International
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Society for Computer Simulation International
San Diego, CA, United States
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Published: 12 April 2015
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