Coarse grain (CG) molecular models have been proposed to simulate complex sys- tems with lower computational overheads and longer timescales with respect to atom- istic level models. However, their acceleration on parallel architectures such as Graphic Processing Units (GPU) presents original challenges that must be carefully evaluated. The objective of this work is to characterize the impact of CG model features on parallel simulation performance. To achieve this, we implemented a GPU-accelerated version of a CG molecular dynamics simulator, to which we applied specic optimizations for CG models, such as dedicated data structures to handle dierent bead type interac- tions, obtaining a maximum speed-up of 14 on the NVIDIA GTX480 GPU with Fermi architecture. We provide a complete characterization and evaluation of algorithmic and simulated system features of CG models impacting the achievable speed-up and accuracy of results, using three dierent GPU architectures as case studies.

Acceleration of Coarse Grain Molecular Dynamics on GPU Architectures / Shkurti, Ardita; Mario, Orsi; Macii, Enrico; Ficarra, Elisa; Acquaviva, Andrea. - In: JOURNAL OF COMPUTATIONAL CHEMISTRY. - ISSN 0192-8651. - 34:10(2013), pp. 803-818. [10.1002/jcc.23183]

Acceleration of Coarse Grain Molecular Dynamics on GPU Architectures

FICARRA, ELISA;
2013

Abstract

Coarse grain (CG) molecular models have been proposed to simulate complex sys- tems with lower computational overheads and longer timescales with respect to atom- istic level models. However, their acceleration on parallel architectures such as Graphic Processing Units (GPU) presents original challenges that must be carefully evaluated. The objective of this work is to characterize the impact of CG model features on parallel simulation performance. To achieve this, we implemented a GPU-accelerated version of a CG molecular dynamics simulator, to which we applied specic optimizations for CG models, such as dedicated data structures to handle dierent bead type interac- tions, obtaining a maximum speed-up of 14 on the NVIDIA GTX480 GPU with Fermi architecture. We provide a complete characterization and evaluation of algorithmic and simulated system features of CG models impacting the achievable speed-up and accuracy of results, using three dierent GPU architectures as case studies.
2013
34
10
803
818
Acceleration of Coarse Grain Molecular Dynamics on GPU Architectures / Shkurti, Ardita; Mario, Orsi; Macii, Enrico; Ficarra, Elisa; Acquaviva, Andrea. - In: JOURNAL OF COMPUTATIONAL CHEMISTRY. - ISSN 0192-8651. - 34:10(2013), pp. 803-818. [10.1002/jcc.23183]
Shkurti, Ardita; Mario, Orsi; Macii, Enrico; Ficarra, Elisa; Acquaviva, Andrea
File in questo prodotto:
File Dimensione Formato  
jccSHKURTI.pdf

Accesso riservato

Dimensione 6.55 MB
Formato Adobe PDF
6.55 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Shkurti_Journal_of_Computational_Chemistry.pdf

Accesso riservato

Dimensione 1.19 MB
Formato Adobe PDF
1.19 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1240404
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
social impact