Type of Document	Master's Thesis
Author	Muthukrishnan, Gayathri
Author's Email Address	gmuthukr@vt.edu
URN	etd-05222004-091126
Title	Utilizing Hierarchical Clusters in the Design of Effective and Efficient Parallel Simulations of 2-D and 3-D Ising Spin Models
Degree	Master of Science
Department	Computer Science
Advisory Committee	Advisor Name Title Santos, Eunice E. Committee Chair Jones, Mark T. Committee Member Ribbens, Calvin J. Committee Member
Keywords	Ising model hierarchical clusters LogP model parallel computing performance analysis & prediction
Date of Defense	2004-05-12
Availability	unrestricted
Abstract In this work, we design parallel Monte Carlo algorithms for the Ising spin model on a hierarchical cluster. A hierarchical cluster can be considered as a cluster of homogeneous nodes which are partitioned into multiple supernodes such that communication across homogenous clusters is represented by a supernode topological network. We consider different data layouts and provide equations for choosing the best data layout under such a network paradigm. We show that the data layouts designed for a homogeneous cluster will not yield results as good as layouts designed for a hierarchical cluster. We derive theoretical results on the performance of the algorithms on a modified version of the LogP model that represents such tiered networking, and present simulation results to analyze the utility of the theoretical design and analysis. Furthermore, we consider the 3-D Ising model and design parallel algorithms for sweep spin selection on both homogeneous and hierarchical clusters. We also discuss the simulation of hierarchical clusters on a homogeneous set of machines, and the efficient implementation of the parallel Ising model on such clusters.
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