Chris Brown is a Senior Research Fellow at the University of St Andrews working in the area of Refactoring and Parallelism. Chris received his Ph.D. from the University of Kent in 2008 under the supervision of Simon Thompson, where he worked on the implementation of the HaRe refactoring tool for Haskell. Chris now works towards building radically new refactoring techniques and methodologies to exploit parallel skeleton and pattern applications in both the functional and imperative domains. Chris has published at major conferences in the field of functional programming, refactoring and parallelism.
Modern multicore systems offer huge computing potential. Exploiting large parallel systems is still a very challenging task, however, especially as many software developers still use overly-sequential programming models. In this talk, I will present a radical and novel approach to introducing and tuning parallelism for heterogeneous shared-memory systems (comprising a mixture of CPUs and GPUs), that combines algorithmic skeletons, machine-learning, and refactoring tool support. Specifically, I will show how to use skeletons to model the parallelism, machine learning to predict the optimal configuration and mapping and refactoring to introduce the parallelism into the application. Finally, I will demonstrate our tools on a number of applications, showing that we can easily obtain comparable results to hand-tuned optimised versions.