The enormous computing resources that large-scale simulations in Lattice QCD
require will continue to test the limits of even the largest supercomputers into
the foreseeable future. The efficiency of such simulations will therefore concern
practitioners of lattice QCD for some time to come.
I begin with an introduction to those aspects of lattice QCD essential to the
remainder of the thesis, and follow with a description of the Wilson fermion
matrix M, an object which is central to my theme.
The principal bottleneck in Lattice QCD simulations is the solution of linear
systems involving M, and this topic is treated in depth. I compare some of the
more popular iterative methods, including Minimal Residual, Corij ugate Gradient
on the Normal Equation, BI-Conjugate Gradient, QMR., BiCGSTAB and
BiCGSTAB2, and then turn to a study of block algorithms, a special class of iterative
solvers for systems with multiple right-hand sides. Included in this study
are two block algorithms which had not previously been applied to lattice QCD.
The next chapters are concerned with a generalised Hybrid Monte Carlo algorithm
(OHM C) for QCD simulations involving dynamical quarks. I focus squarely
on the efficient and robust implementation of GHMC, and describe some tricks
to improve its performance. A limited set of results from HMC simulations at
various parameter values is presented.
A treatment of the non-hermitian Lanczos method and its application to the
eigenvalue problem for M rounds off the theme of large-scale matrix computations
