Parallel Fast Multipole Method for Molecular Dynamics

We report on a parallel version of the Fast Multipole Method (FMM) implemented in the classical molecular dynamics code, NAMD (Not Another Molecular Dynamics program). This novel implementation of FMM aims to minimize interprocessor communication through the modification of the FMM grid to match the hybrid force and spatial decomposition scheme already present in NAMD. This new implementation has the benefit of replacing all-to-all communications broadcasts with direct communications between nearest neighbors. This results in a significant reduction in the amount of communication compared to earlier attempts to integrate FMM into common molecular dynamics programs. The early performance of FMM is similar to the existing electrostatics methods already in NAMD. In addition, tests of the stability and accuracy of the FMM algorithm in molecular dynamics as applied to several common solvated protein structures are discussed

Computational Physics on Graphics Processing Units

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics, and on quantum simulations for electronic structure calculations using the density functional theory, wave function techniques, and quantum field theory.Comment: Proceedings of the 11th International Conference, PARA 2012, Helsinki, Finland, June 10-13, 201

Developing performance-portable molecular dynamics kernels in Open CL

This paper investigates the development of a molecular dynamics code that is highly portable between architectures. Using OpenCL, we develop an implementation of Sandia’s miniMD benchmark that achieves good levels of performance across a wide range of hardware: CPUs, discrete GPUs and integrated GPUs. We demonstrate that the performance bottlenecks of miniMD’s short-range force calculation kernel are the same across these architectures, and detail a number of platform- agnostic optimisations that improve its performance by at least 2x on all hardware considered. Our complete code is shown to be 1.7x faster than the original miniMD, and at most 2x slower than implementations individually hand-tuned for a specific architecture

Acceleration of Coarse Grain Molecular Dynamics on GPU Architectures

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 studie

Efficient swap algorithms for molecular dynamics simulations of equilibrium supercooled liquids

It was recently demonstrated that a simple Monte Carlo (MC) algorithm involving the swap of particle pairs dramatically accelerates the equilibrium sampling of simulated supercooled liquids. We propose two numerical schemes integrating the efficiency of particle swaps into equilibrium molecular dynamics (MD) simulations. We first develop a hybrid MD/MC scheme combining molecular dynamics with the original swap Monte Carlo. We implement this hybrid method in LAMMPS, a software package employed by a large community of users. Secondly, we define a continuous time version of the swap algorithm where both the positions and diameters of the particles evolve via Hamilton's equations of motion. For both algorithms, we discuss in detail various technical issues as well as the optimisation of simulation parameters. We compare the numerical efficiency of all available swap algorithms and discuss their relative merits.Comment: 16 pages, 13 figure