GPGPU-accelerated environmental modelling based on the 2D advection-reaction-diffusion equation. (June 2019)

• Record Type: Journal Article
• Authors: Carlotto, T.; da Silva, R.V.; Grzybowski, J.M.V.
• Is Part Of: Environmental modelling & software. Volume 116(2019)
• Page Start: 87
• Page End: 99
• Publication Date: 2019-06
• Subjects: Advection-reaction-diffusion equation -- High-performance computing -- CUDA™; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2019.02.001
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The advection-reaction-diffusion equation is a rather general model that describes a variety of environmental processes, such as air pollution transport, aquifer recharge, groundwater contaminant transport and forest growth, among others. The resulting models are known to be computationally demanding, especially when the model covers large areas where in high resolution. In this context, the exponential increase in computational power of massively parallel computing devices, such as the General Purpose Graphics Processing Units (GPGPUs), has triggered a paradigm shift in scientific computing and environmental modelling. In this paper we present an environmental modelling solution based on a parallel implementation of the 2D advection-reaction-diffusion equation, tailored for GPGPU devices. The software is flexible, free, open-source and allows the modelling of a wide range of environmental phenomena, including those taking place in heterogeneous and anisotropic media. Performance tests show that the parallel GPU implementation can provide up to a 70-fold speedup in relation to an analogous CPU implementation. Highlights: PARMOD2D can be applied to a broad class of environmental models based on the Advection-Reaction-Diffusion equation. The GPGPU-accelerated implementation provides up to a 70-fold speedup in processing time. This GPGPU-accelerated framework for environmental models can deliver fast and accurate solutions to large-scale grids.