First Experiences on an Accurate SPH Method on GPUs

Marta Paliaga, Elisa Francomano, Ardelio Galletti, Livia Marcellino

Risultato della ricerca: Other

1 Citazione (Scopus)

Abstract

t is well known that the standard formulation of the Smoothed Particle Hydrodynamics is usually poor when scattered data distribution is considered or when the approximation near the boundary occurs. Moreover, the method is computational demanding when a high number of data sites and evaluation points are employed. In this paper an enhanced version of the method is proposed improving the accuracy and the efficiency by using a HPC environment. Our implementation exploits the processing power of GPUs for the basic computational kernel resolution. The performance gain demonstrates the method to be accurate and suitable to deal with large sets of data.
Lingua originaleEnglish
Pagine445-449
Numero di pagine5
Stato di pubblicazionePublished - 2018

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Computational methods
Hydrodynamics
Processing
Graphics processing unit

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cita questo

First Experiences on an Accurate SPH Method on GPUs. / Paliaga, Marta; Francomano, Elisa; Galletti, Ardelio; Marcellino, Livia.

2018. 445-449.

Risultato della ricerca: Other

Paliaga, M, Francomano, E, Galletti, A & Marcellino, L 2018, 'First Experiences on an Accurate SPH Method on GPUs', pagg. 445-449.
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N2 - t is well known that the standard formulation of the Smoothed Particle Hydrodynamics is usually poor when scattered data distribution is considered or when the approximation near the boundary occurs. Moreover, the method is computational demanding when a high number of data sites and evaluation points are employed. In this paper an enhanced version of the method is proposed improving the accuracy and the efficiency by using a HPC environment. Our implementation exploits the processing power of GPUs for the basic computational kernel resolution. The performance gain demonstrates the method to be accurate and suitable to deal with large sets of data.

AB - t is well known that the standard formulation of the Smoothed Particle Hydrodynamics is usually poor when scattered data distribution is considered or when the approximation near the boundary occurs. Moreover, the method is computational demanding when a high number of data sites and evaluation points are employed. In this paper an enhanced version of the method is proposed improving the accuracy and the efficiency by using a HPC environment. Our implementation exploits the processing power of GPUs for the basic computational kernel resolution. The performance gain demonstrates the method to be accurate and suitable to deal with large sets of data.

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