# LAMMPS' PPPM Long-Range Solver for the Second Generation Xeon Phi

## TL;DR

This paper presents optimized PPPM long-range solver implementation in LAMMPS for the second-generation Intel Xeon Phi, achieving significant kernel speedups and overall performance improvements for molecular dynamics simulations involving charged particles.

## Contribution

The paper introduces a vectorized implementation of the PPPM solver in LAMMPS optimized for Xeon Phi, enabling faster simulations without retuning parameters.

## Key findings

- Kernel speedups of up to 12x
- Overall simulation speedups of 2-3x
- Simplified parameter tuning process

## Abstract

Molecular Dynamics is an important tool for computational biologists, chemists, and materials scientists, consuming a sizable amount of supercomputing resources. Many of the investigated systems contain charged particles, which can only be simulated accurately using a long-range solver, such as PPPM. We extend the popular LAMMPS molecular dynamics code with an implementation of PPPM particularly suitable for the second generation Intel Xeon Phi. Our main target is the optimization of computational kernels by means of vectorization, and we observe speedups in these kernels of up to 12x. These improvements carry over to LAMMPS users, with overall speedups ranging between 2-3x, without requiring users to retune input parameters. Furthermore, our optimizations make it easier for users to determine optimal input parameters for attaining top performance.