RESEARCH SUMMARY

Dr Coddington has been working in the area of computational science and parallel computing for more than 8 years, almost from the beginnings of applied parallel computation in the early 80’s. He obtained a Bachelor of Science degree with first class honors from the University of Western Australia in 1982, and his Ph.D. in 1988 from Southampton University, one of the leading universities in England for research in parallel computing. He is a member of the American Physical Society.

Dr Coddington’s original research includes contributions to both theoretical and computational physics, in particular the development of new algorithms for parallel computers. His research on lattice gauge theory and the quantum Hall effect was among the earliest work in these fields to use high performance parallel computers. His work on new techniques for gauge fixing in lattice gauge theory has been cited in many recent publications, as interest in this method has increased greatly in the last few years. He has contributed to the study of solid state physics, spin models, gauge theories, and quantum gravity, and especially the computer simulation of these problems. He pioneered the development of parallel algorithms for some of these problems, especially cluster Monte Carlo methods. Use of these algorithms on parallel supercomputers has enabled accurate measurements of the dynamic critical exponents of cluster Monte Carlo algorithms to be performed, which is important for understanding the mechanism by which these new algorithms work. The same parallel algorithms can also be used for connected component labeling, which is an important part of image processing and computer vision. These algorithms are archetypal irregular problems which also provide important benchmark tests for parallel hardware, software and languages.

Dr Coddington is considered an expert in parallel algorithms for computational science, particularly in the field of Monte Carlo simulation. He has also worked on parallel algorithms for solving matrix problems and partial differential equations, in particular porting existing sequential programs to parallel computers. He has experience in using a wide variety of parallel computers, including the DAP, Meiko Computing Surface, nCUBE/10 and nCUBE/2, Symult 2010, Encore Multimax, Sequent Symmetry, BBN Butterfly, Intel Delta, CM-2, CM-5, MasPar, and workstation networks; and almost as many parallel languages, including Occam, DAP Fortran, CM Fortran, MasPar Fortran, *Lisp, C*, MPL, and Express C and Fortran.

Dr Coddington has had 9 papers published in leading international journals in both physics (Physical Review B, Physical Review Letters, Nuclear Physics B, Physics Letters B, Journal of Physics C, Europhysics Letters) and computational science (Concurrency: Practice and Experience, International Journal of Modern Physics C), and had 10 papers published in the proceedings of international conferences on computational science.

Dr Coddington has been asked to review the work of others in similar academic fields, by refereeing papers of other authors for international journals (Physical Review, International Journal of Modern Physics) and conferences (The International Symposium on High Performance Distributed Computing).

Dr Coddington’s work has been cited by other researchers in 11 publications in international journals prior to this year. His more recent research on parallel algorithms for cluster Monte Carlo methods is pioneering work in this field, and has been cited in at least 3 recent unpublished papers, and in one case formed the basis for that research.

Dr Coddington is currently employed as a Research Scientist at the Northeast Parallel Architectures Center (NPAC) at Syracuse University. He is leading a project to study the use of high performance parallel computing in the power utility industry, to develop new parallel algorithms for the simulation of power networks, and to port existing sequential programs to parallel computers. This includes the development and implementation of parallel algorithms for sparse matrix computations and differential-algebraic equation solvers, which are also applicable to a number of other industrial applications. This work is expected to greatly improve the accuracy of computer simulations of power grids, and to consequently improve the reliability and efficiency of electrical power generation and distribution. This project is part of ACTION, NPAC’s industrial outreach program. Dr Coddington has had previous experience working with the Transputer Support Center, a similar program associated with Southampton University, which provides a consultancy and teaching facility aimed at increasing the use of parallel computing by industry.