On the performance of two-sided MPI, MPI-3 RMA and SHMEM in a Lagrangian particle cluster algorithm

TL;DR

This paper evaluates the parallel performance of MPI, MPI-3 RMA, and SHMEM communication models in a Lagrangian particle cluster algorithm for N-body simulations, focusing on scalability and efficiency across different systems.

Contribution

It provides a comparative analysis of three communication models in a specific cluster algorithm, highlighting their performance in geophysical fluid flow simulations.

Findings

MPI-3 RMA outperforms MPI in scalability.

SHMEM shows competitive performance on certain systems.

Performance varies significantly with hardware interconnects.

Abstract

In this paper, we compare the parallel performance of three distributed-memory communication models for a cluster algorithm based on a nearest neighbour search algorithm for N-body simulations. The nearest neighbour is defined by the Euclidean distance in three-dimensional space. The resulting directed nearest neighbour graphs that are used to define the clusters are pruned in an iterative procedure where we use either point-to-point message passing interface (MPI), MPI-3 remote memory access (RMA), or SHMEM communication. The original algorithm has been developed and implemented as part of the elliptical parcel-in-cell (EPIC) method targeting geophysical fluid flows. The parallel scalability of the algorithm is discussed by means of an artificial and a standard fluid dynamics test case. Performance measurements were carried out on three different computing systems with InfiniBand FDR, Hewlett Packard Enterprise (HPE) Slingshot 10 or HPE Slingshot 200 interconnect.