Recovering historical climate records using artificial neural networks in GPU
- Autor(es):
- Balarini, Juan Pablo ; Nesmachnow, Sergio
- Tipo:
- Reporte técnico
- Versión:
- Publicado
- Resumen:
-
This article presents a parallel implementation of Artificial Neural Networks over Graphic Processing Units, and its application for recovering his-torical climate records from the Digi-Clima project. Several strategies are intro-duced to handle large volumes of historical pluviometer records, and the paral-lel deployment is described. The experimental evaluation demonstrates that the proposed approach is useful for recovering the climate information, achieving classification rates up to 76% for a set of real images from the Digi-Clima pro-ject. The parallel algorithm allows reducing the execution times, with an accel-eration factor of up to 2.15×.
- Año:
- 2014
- Idioma:
- Inglés
- Temas:
- Artificial neural networks
Image processing
Climate records
GPU
- Institución:
- Universidad de la República
- Repositorio:
- COLIBRI
- Enlace(s):
- http://hdl.handle.net/20.500.12008/5169
- Nivel de acceso:
- Acceso abierto