Efficient Parallel Simulations of Asynchronous Cellular Arrays

TL;DR

This paper introduces efficient parallel algorithms for simulating asynchronous cellular arrays, including the Ising model, demonstrating significant speed-ups on various computing architectures and challenging the belief that serial algorithms lack parallel counterparts.

Contribution

The paper presents novel parallel algorithms for asynchronous cellular arrays, including the Ising model, with proven efficiency and substantial speed-ups, contradicting previous assumptions.

Findings

Speed-up greater than 16 with 25 PEs on shared memory systems

Speed-up greater than 1900 with 2^14 PEs on SIMD computers

Incorporation of Bortz-Kalos-Lebowitz algorithm enhances performance

Abstract

A definition for a class of asynchronous cellular arrays is proposed. An example of such asynchrony would be independent Poisson arrivals of cell iterations. The Ising model in the continuous time formulation of Glauber falls into this class. Also proposed are efficient parallel algorithms for simulating these asynchronous cellular arrays. In the algorithms, one or several cells are assigned to a processing element (PE), local times for different PEs can be different. Although the standard serial algorithm by Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller can simulate such arrays, it is usually believed to be without an efficient parallel counterpart. However, the proposed parallel algorithms contradict this belief proving to be both efficient and able to perform the same task as the standard algorithm. The results of experiments with the new algorithms are encouraging: the speed-up is greater than 16 using 25 PEs on a shared memory MIMD bus computer, and greater than 1900 using 2**14 PEs on a SIMD computer. The algorithm by Bortz, Kalos, and Lebowitz can be incorporated in the proposed parallel algorithms, further contributing to speed-up. [In this paper I invented the update-cites-of-local-time-minima parallel simulation scheme. Now the scheme is becoming popular. Many misprints of the original 1987 Complex Systems publication are corrected here.-B.L.]