A Parallel Implementation of the Species Distribution Modeling Algorithm

Autor: Alfredo Cristóbal-Salas, Sara Patricia Ibarra-Zavaleta, Bardo Santiago-Vicente, Israel Estrada-Contreras
Rok vydání: 2019
Předmět:
Zdroj: 2019 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC).
Popis: Climate change together with changes in the atmosphere´s chemical composition are causing serious alterations in several ecosystems. These risks are mainly due to greenhouse gases concentrations, variation in rainfall periods, and the increase in the average temperature of the planet. The effects of these environmental problems have an impact on the distribution of several species. A strategy to know the affectations of these variables in the species distribution is presented in this paper. This strategy is implemented as a parallel version of a supervised classification technique called MaxLike. This parallel code runs in a Linux Centos OS based computer with 1,120 cores, 3 TB RAM. This parallel algorithm reaches a speedup of 12.56 with 16 cores configuration which improves significatively the execution time allowing a more extensive analysis of species distribution and a longer simulation over the time.
Databáze: OpenAIRE