Title page for ETD etd-12182001-234435


Type of Document Master's Thesis
Author Feng, Shuangtong
Author's Email Address sfeng@vt.edu
URN etd-12182001-234435
Title Efficient Parallelization of 2D Ising Spin Systems
Degree Master of Science
Department Computer Science
Advisory Committee
Advisor Name Title
Santos, Eunice E. Committee Chair
Heath, Lenwood S. Committee Member
Ribbens, Calvin J. Committee Member
Keywords
  • spin selection schemes
  • data layout optimization
  • computational science
  • Ising model
  • LogP parallel model
  • performance prediction
  • parallel and distributed processing
Date of Defense 2001-12-11
Availability unrestricted
Abstract
The problem of efficient parallelization of 2D Ising spin systems requires realistic algorithmic design and implementation based on an understanding of issues from computer science and statistical physics. In this work, we not only consider fundamental parallel computing issues but also ensure that the major constraints and criteria of 2D Ising spin systems are incorporated into our study. This realism in both parallel computation and statistical physics has rarely been reflected in previous research for this problem.

In this thesis,we designed and implemented a variety of parallel algorithms for both sweep spin selection and random spin selection. We analyzed our parallel algorithms on a portable and general parallel machine model, namely the LogP model. We were able to obtain rigorous theoretical run-times on LogP for all the parallel algorithms. Moreover, a guiding equation was derived for choosing data layouts (blocked vs. stripped) for sweep spin selection. In regards to random spin selection, we were able to develop parallel algorithms with efficient communication schemes. We analyzed randomness of our schemes using statistical methods and provided comparisons between the different schemes. Furthermore, algorithms were implemented and performance data gathered and analyzed in order to determine further design issues and validate theoretical analysis.

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