N-Body simulation using GP-GPU: evaluating host/device memory transference overhead

N-Body simulation algorithms are amongst the most commonly used within the field of scientific computing. Especially in computational astrophysics, they are used to simulate gravitational scenarios for solar systems or galactic collisions. Parallel versions of such N-Body algorithms have been extens...

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Detalles Bibliográficos
Autores principales: Martín, Sergio, Tinetti, Fernando Gustavo, Casas, Nicanor, De Luca, Graciela, Giulianelli, Daniel Alberto
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2013
Materias:
Ciencias Informáticas
Simulation
Optimization
N-Body simulation
GPU optimization
data transference overhead
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/31704
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-31704
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Simulation
Optimization
N-Body simulation
GPU optimization
data transference overhead
spellingShingle Ciencias Informáticas
Simulation
Optimization
N-Body simulation
GPU optimization
data transference overhead
Martín, Sergio
Tinetti, Fernando Gustavo
Casas, Nicanor
De Luca, Graciela
Giulianelli, Daniel Alberto
N-Body simulation using GP-GPU: evaluating host/device memory transference overhead
topic_facet Ciencias Informáticas
Simulation
Optimization
N-Body simulation
GPU optimization
data transference overhead
description N-Body simulation algorithms are amongst the most commonly used within the field of scientific computing. Especially in computational astrophysics, they are used to simulate gravitational scenarios for solar systems or galactic collisions. Parallel versions of such N-Body algorithms have been extensively designed and optimized for multicore and distributed computing schemes. However, N-Body algorithms are still a novelty in the field of GPGPU computing. Although several N-body algorithms have been proved to harness the potential of a modern GPU processor, there are additional complexities that this architecture presents that could be analyzed for possible optimizations. In this article, we introduce the problem of host to device (GPU) – and vice versa – data transferring overhead and analyze a way to estimate its impact in the performance of simulations.
format Objeto de conferencia
Objeto de conferencia
author Martín, Sergio
Tinetti, Fernando Gustavo
Casas, Nicanor
De Luca, Graciela
Giulianelli, Daniel Alberto
author_facet Martín, Sergio
Tinetti, Fernando Gustavo
Casas, Nicanor
De Luca, Graciela
Giulianelli, Daniel Alberto
author_sort Martín, Sergio
title N-Body simulation using GP-GPU: evaluating host/device memory transference overhead
title_short N-Body simulation using GP-GPU: evaluating host/device memory transference overhead
title_full N-Body simulation using GP-GPU: evaluating host/device memory transference overhead
title_fullStr N-Body simulation using GP-GPU: evaluating host/device memory transference overhead
title_full_unstemmed N-Body simulation using GP-GPU: evaluating host/device memory transference overhead
title_sort n-body simulation using gp-gpu: evaluating host/device memory transference overhead
publishDate 2013
url http://sedici.unlp.edu.ar/handle/10915/31704
work_keys_str_mv AT martinsergio nbodysimulationusinggpgpuevaluatinghostdevicememorytransferenceoverhead
AT tinettifernandogustavo nbodysimulationusinggpgpuevaluatinghostdevicememorytransferenceoverhead
AT casasnicanor nbodysimulationusinggpgpuevaluatinghostdevicememorytransferenceoverhead
AT delucagraciela nbodysimulationusinggpgpuevaluatinghostdevicememorytransferenceoverhead
AT giulianellidanielalberto nbodysimulationusinggpgpuevaluatinghostdevicememorytransferenceoverhead
bdutipo_str Repositorios
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