Efficient Parallel Cell List Algorithms for Monte Carlo Simulations (WIP)

摘要

Designing efficient algorithms for many-core and multicore architectures requires using different strategies to allow for the best exploitation of the hardware resources on those architectures. This work describes efficient many-core and multicore large-scale energy calculations for Monte Carlo Gibbs ensemble using cell lists. Designing Monte Carlo molecular simulations is challenging as they have less computation and parallelism when compared to similar molecular dynamics applications. Our modified cell list allows for more speedup gains for energy calculations on both many-core and multicore architectures when compared to other implementations without using the conventional cell lists. We present our results and analysis of the cell list algorithms for each one of the parallel architectures using top of the line GPUs, CPUs, and Intel's Phi coprocessors. We evaluate the performance of the cell list algorithms for different problem sizes and different radial cutoffs.