Programs in Physics & Physical Chemistry
|[Licence| Download | New Version Template] aetn_v1_0.tar.gz(25868 Kbytes)|
|Manuscript Title: Accelerating Dissipative Particle Dynamics Simulations on GPUs: Algorithms, Numerics and Applications|
|Authors: Yu-Hang Tang, George Em Karniadakis|
|Program title: GPU-accelerated DPD Package for LAMMPS|
|Catalogue identifier: AETN_v1_0|
Distribution format: tar.gz
|Journal reference: Comput. Phys. Commun. 185(2014)2809|
|Programming language: C/C++, CUDA C/C++, MPI.|
|Computer: Any computers having nVidia GPGPUs with compute capability 3.0.|
|Operating system: Linux.|
|Has the code been vectorised or parallelized?: Yes. Number of processors used: 1024 16-core CPUs and 1024 GPUs|
|RAM: 500 Mbytes host memory, 2 Gbytes device memory|
|Supplementary material: The data for the examples discussed in the manuscript is available for download.|
|Keywords: DPD CUDA LAMMPS spontaneous vesicle formation.|
|PACS: 47.11.Mn, 87.10.Tf, 87.15.ap, 68.65.-k.|
|Classification: 6.5, 12, 16.1, 16.11.|
Nature of problem:
Particle-based simulation of mesoscale systems involving nano/micro-fluids, polymers and spontaneous self-assembly process.
The system is approximated by a number of coarse-grained particles interacting through pairwise potentials and bonded potentials. Classical mechanics is assumed following Newton's laws. The evolution of the system is integrated using a time-stepping scheme such as Velocity-Verlet.
The code runs only on CUDA GPGPUs with compute capability 3.0.
Fully implemented on GPGPUs with signicant speedup.
78 hours using 1024 GPGPUs for simulating a 128-million-particle system for 18.4 million time steps.
|Disclaimer | ScienceDirect | CPC Journal | CPC | QUB|