PySPH: a reproducible and high-performance framework for smoothed particle hydrodynamics

Abstract

Smoothed Particle Hydrodynamics (SPH) is a general purpose tech- nique to numerically compute the solutions to partial differential equations such as those used to simulate fluid and solid mechanics. The method is grid-free and uses particles to discretize the various properties of interest (such as density, fluid velocity, pressure etc.). The method is Lagrangian and particles are moved with the local velocity. PySPH is an open source framework for Smoothed Particle Hydrodynamics. It is implemented in a mix of Python and Cython. It is designed to be easy to use on multiple platforms, high-performance and support parallel execution. Users write pure-Python code and HPC code is generated on the fly, compiled, and executed. PySPH supports OpenMP and MPI for distributed computing, in a way that is transparent to the user. PySPH is also designed to make it easy to perform reproducible research. In this paper we discuss the design and implementation of PySPH.