English

Ethane: A Heterogeneous Parallel Search Algorithm for Heterogeneous Platforms

Neural and Evolutionary Computing 2011-06-01 v2 Distributed, Parallel, and Cluster Computing

Abstract

In this paper we present Ethane, a parallel search algorithm specifically designed for its execution on heterogeneous hardware environments. With Ethane we propose an algorithm inspired in the structure of the chemical compound of the same name, implementing a heterogeneous island model based in the structure of its chemical bonds. We also propose a schema for describing a family of parallel heterogeneous metaheuristics inspired by the structure of hydrocarbons in Nature, HydroCM (HydroCarbon inspired Metaheuristics), establishing a resem- blance between atoms and computers, and between chemical bonds and communication links. Our goal is to gracefully match computers of different power to algorithms of different behavior (GA and SA in this study), all them collaborating to solve the same problem. The analysis will show that Ethane, though simple, can solve search problems in a faster and more robust way than well-known panmitic and distributed algorithms very popular in the literature.

Keywords

Cite

@article{arxiv.1105.5900,
  title  = {Ethane: A Heterogeneous Parallel Search Algorithm for Heterogeneous Platforms},
  author = {Julián Domínguez and Enrique Alba},
  journal= {arXiv preprint arXiv:1105.5900},
  year   = {2011}
}

Comments

Paper 6 for the First International Workshop of Distributed Evolutionary computation in Informal Environments

R2 v1 2026-06-21T18:14:26.969Z