PetFMM--A dynamically load-balancing parallel fast multipole library

TL;DR

PetFMM is an extensible, parallel fast multipole method library built on PETSc, featuring automatic load balancing, high scalability, and efficiency for large N-body simulations, facilitating scientific computing development.

Contribution

The paper introduces PetFMM, a novel parallel FMM library with automatic load balancing and extensibility, improving scalability and ease of integration for scientific applications.

Findings

Achieves over 85% parallel efficiency on 64 processors.

Supports near a million particles with strong scaling performance.

Provides a comprehensive model for load balancing and communication in parallel N-body algorithms.

Abstract

Fast algorithms for the computation of $N$-body problems can be broadly classified into mesh-based interpolation methods, and hierarchical or multiresolution methods. To this last class belongs the well-known fast multipole method (FMM), which offers O(N) complexity. This paper presents an extensible parallel library for $N$-body interactions utilizing the FMM algorithm, built on the framework of PETSc. A prominent feature of this library is that it is designed to be extensible, with a view to unifying efforts involving many algorithms based on the same principles as the FMM and enabling easy development of scientific application codes. The paper also details an exhaustive model for the computation of tree-based $N$-body algorithms in parallel, including both work estimates and communications estimates. With this model, we are able to implement a method to provide automatic, a priori load balancing of the parallel execution, achieving optimal distribution of the computational work among processors and minimal inter-processor communications. Using a client application that performs the calculation of velocity induced by $N$ vortex particles, ample verification and testing of the library was performed. Strong scaling results are presented with close to a million particles in up to 64 processors, including both speedup and parallel efficiency. The library is currently able to achieve over 85% parallel efficiency for 64 processors. The software library is open source under the PETSc license; this guarantees the maximum impact to the scientific community and encourages peer-based collaboration for the extensions and applications.