Acceleration of Dynamic n-Tuple Computations in Many-Body Molecular Dynamics

Computation on dynamic n-tuples of particles is ubiquitous in scientific computing, with an archetypal application in many-body molecular dynamics (MD) simulations. We propose a tuple-decomposition (TD) approach that reorders computations according to dynamically created lists of n-tuples. We analyze the performance characteristics of the TD approach on general purpose graphics processing units for MD simulations involving pair (n = 2) and triplet (n = 3) interactions. The results show superior performance of the TD approach over the conventional particle-decomposition (PD) approach. Detailed analyses reveal the register footprint as the key factor that dictates the performance. Furthermore, the TD approach is found to outperform PD for more intensive computations of quadruplet (n = 4) interactions in first principles-informed reactive MD simulations based on the reactive force-field (ReaxFF) method. This work thus demonstrates the viable performance portability of the TD approach across a wide range of applications.