(377j) Efficient Neighbor List Calculation for Molecular Simulation of Colloidal Systems Using Graphics Processing Units
AIChE Annual Meeting
Tuesday, November 15, 2016 - 2:44pm to 2:56pm
Calculation of the forces between particles, and in particular, nonbonded pair interactions, dominates the computational time of the MD algorithm. In order to accelerate these calculations, pair potentials are frequently truncated at a finite cutoff distance, and a neighbor (Verlet) list of particles within each othersâ??s cutoffs is maintained to reduce the number of distance evaluations between particles that are performed. The calculation of the neighbor list itself is accelerated using a structure such as a spatially-binned cell list that reduces the overall computational complexity of the algorithm.
We present an algorithm based on linear bounding volume hierarchies (LBVHs) for computing neighbor (Verlet) lists using graphics processing units (GPUs) for colloidal systems characterized by large size disparities. We compare this in the HOOMD-blue simulation package to a GPU implementation of the current state-of-the-art CPU algorithm based on stenciled cell lists. We report benchmarks for both neighbor list algorithms in a Lennard-Jones binary mixture with synthetic interaction range disparity and a realistic colloid solution. LBVHs outperform the stenciled cell lists for systems with moderate or large size disparity and dilute or semidilute fractions of large particles, conditions typical of colloidal systems. The LBVH neighbor list algorithm has recently been applied to study transport and structure formation in colloidal dispersions under flow.