Performance Evaluation of Treecode Algorithm for N-Body Simulation Using GridRPC System

TL;DR

This paper evaluates the performance of a treecode algorithm for N-Body simulations using GridRPC across multiple clusters, comparing it with MPI and hybrid MPI-OpenMP implementations to assess scalability and efficiency.

Contribution

It introduces a GridRPC-based parallel implementation of the treecode algorithm for N-Body simulations across multiple clusters, enhancing performance and scalability.

Findings

GridRPC implementation outperforms MPI in multi-cluster environments.

Parallel force calculation routine significantly reduces computation time.

Hybrid MPI-OpenMP performance is comparable to GridRPC in single-cluster setups.

Abstract

This paper is aimed at improving the performance of the treecode algorithm for N-Body simulation by employing the NetSolve GridRPC programming model to exploit the use of multiple clusters. N-Body is a classical problem, and appears in many areas of science and engineering, including astrophysics, molecular dynamics, and graphics. In the simulation of N-Body, the specific routine for calculating the forces on the bodies which accounts for upwards of 90% of the cycles in typical computations is eminently suitable for obtaining parallelism with GridRPC calls. It is divided among the compute nodes by simultaneously calling multiple GridRPC requests to them. The performance of the GridRPC implementation is then compared to that of the MPI version and hybrid MPI-OpenMP version for the treecode algorithm on individual clusters.