Predictive analysis and optimisation of pipelined wavefront computations

Pipelined wavefront computations are a ubiquitous class of parallel algorithm used for the solution of a number of scientific and engineering applications. This paper investigates three optimisations to the generic pipelined wavefront algorithm, which are investigated through the use of predictive analytic models. The modelling of potential optimisations is supported by a recently developed reusable LogGP-based analytic performance model, which allows the speculative evaluation of each optimisation within the context of an industry-strength pipelined wavefront benchmark developed and maintained by the United Kingdom Atomic Weapons Establishment (AWE). The paper details the quantitative and qualitative benefits of: (1) parallelising computation blocks of the wavefront algorithm using OpenMP; (2) a novel restructuring/shifting of computation within the wavefront code and, (3) performing simultaneous multiple sweeps through the data grid.