title: Acceleration of coarse grain molecular dynamics on GPU architectures.
abstract: Coarse grain (CG) molecular models have been proposed to simulate complex systems with lower computational overheads and longer timescales with respect to atomistic level models. However, their acceleration on parallel architectures such as graphic processing units (GPUs) 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 specific optimizations for CG models, such as dedicated data structures to handle different bead type interactions, 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 different GPU architectures as case studies.
authors.affiliation: Department of Control and Computer Engineering, Politecnico di Torino, Torino, Italy C.so Duca degli Abruzzi 24, Turin 10129, Italy. ardita.shkurti@polito.it
authors.forename: Ardita
authors.initials: A
authors.lastname: Shkurti
authors.forename: Mario
authors.initials: M
authors.lastname: Orsi
authors.forename: Enrico
authors.initials: E
authors.lastname: Macii
authors.forename: Elisa
authors.initials: E
authors.lastname: Ficarra
authors.forename: Andrea
authors.initials: A
authors.lastname: Acquaviva
mesh_terms: D000465:Algorithms; D056004:Molecular Dynamics Simulation; D012815:Signal Processing, Computer-Assisted