Parallel implementation of a cellular automata in a hybrid CPU/GPU environment

Cellular Automata (CA) simulations can be used to model multiple systems, in fields like biology, physics and mathematics. In this work, a possible framework to execute a popular CA in hybrid CPU and GPUs (Graphics Processing Units) environments is presented. The inherently parallel nature of CA and...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Millán, Emmanuel N., Martínez, Paula, Gil Costa, Graciela Verónica, Piccoli, María Fabiana, Printista, Alicia Marcela, Bederian, Carlos, García Garino, Carlos, Bringa, Eduardo M.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2013
Materias:
Ciencias Informáticas
general purpose GPU
cellular automata
multi-GPU
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/31730
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
Descripción
Sumario:Cellular Automata (CA) simulations can be used to model multiple systems, in fields like biology, physics and mathematics. In this work, a possible framework to execute a popular CA in hybrid CPU and GPUs (Graphics Processing Units) environments is presented. The inherently parallel nature of CA and the parallelism offered by GPUs makes their combination attractive. Benchmarks are conducted in several hardware scenarios. The use of MPI /OMP is explored for CPUs, together with the use of MPI in GPU clusters. Speed-ups up to 20 x are found when comparing GPU implementations to the serial CPU version of the code.

Ejemplares similares