N-Body Simulations on GPUs

TL;DR

This paper demonstrates how GPUs can be effectively used for N-body simulations, achieving high performance and cost efficiency, thus broadening their application in scientific computing and distributed systems.

Contribution

It introduces a highly optimized GPU algorithm for O(N^2) force calculations, significantly improving performance over CPUs and rivaling specialized hardware.

Findings

Achieved nearly 100 GFlops performance on GPUs

Performance comparable to specialized N-body processors

Cost-effective alternative for large-scale simulations

Abstract

Commercial graphics processors (GPUs) have high compute capacity at very low cost, which makes them attractive for general purpose scientific computing. In this paper we show how graphics processors can be used for N-body simulations to obtain improvements in performance over current generation CPUs. We have developed a highly optimized algorithm for performing the O(N^2) force calculations that constitute the major part of stellar and molecular dynamics simulations. In some of the calculations, we achieve sustained performance of nearly 100 GFlops on an ATI X1900XTX. The performance on GPUs is comparable to specialized processors such as GRAPE-6A and MDGRAPE-3, but at a fraction of the cost. Furthermore, the wide availability of GPUs has significant implications for cluster computing and distributed computing efforts like Folding@Home.