Parallel R-matrix computation

For almost thirty years, sequential R-matrix computation has been used by atomic physics research groups, from around the world, to model collision phenomena involving the scattering of electrons or positrons with atomic or molecular targets. As considerable progress has been made in the understanding of fundamental scattering processes, new data, obtained from more complex calculations, is of current interest to experimentalists. Performing such calculations, however, places considerable demands on the computational resources to be provided by the target machine, in terms of both processor speed and memory requirement. Indeed, in some instances the computational requirements are so great that the proposed R-matrix calculations are intractable, even when utilising contemporary classic supercomputers. Historically, increases in the computational requirements of R-matrix computation were accommodated by porting the problem codes to a more powerful classic supercomputer. Although this approach has been successful in the past, it is no longer considered to be a satisfactory solution due to the limitations of current (and future) Von Neumann machines. As a consequence, there has been considerable interest in the high performance multicomputers, that have emerged over the last decade which appear to offer the computational resources required by contemporary R-matrix research. Unfortunately, developing codes for these machines is not as simple a task as it was to develop codes for successive classic supercomputers. The difficulty arises from the considerable differences in the computing models that exist between the two types of machine and results in the programming of multicomputers to be widely acknowledged as a difficult, time consuming and error-prone task. Nevertheless, unless parallel R-matrix computation is realised, important theoretical and experimental atomic physics research will continue to be hindered. This thesis describes work that was undertaken in response to the challenge of achieving parallel R-matrix computation. The primary objective was to develop parallel codes, targeted at multicomputers, that are capable of performing R-matrix calculations hitherto intractable using classic supercomputers. In particular, Fortran implementations of two internal region methods (the R-matrix Floquet method and the two-dimensional R-matrix propagation method) and three external region methods (the Light-Walker propagation method, the Baluja, Burke and Morgan propagation method and the Variable Phase Method) from four widely utilised R-matrix packages were investigated to ascertain whether, in these cases, parallel R-matrix computation was practicable and, if so, to determine the most effective way to port such codes to contemporary multicomputers. When attempting to develop the parallel codes, a number of computer aided automatic parallelization tools were investigated. These were found to be inadequate. Consequently, a parallelization approach was developed to provide simple guidelines for manual parallelization. This parallelization approach proved effective and efficient parallel versions of the five R-matrix codes were successfully developed. (author)