Performance Portability across Diverse Computer Architectures

Previous studies into performance portability have typically analysed a single application (and its various imple- mentations) in isolation. In this study we explore the wider landscape of performance portability by considering a number of applications from across the space of dwarfs, written in multiple parallel programming models, and across a diverse set of architectures. We apply rigorous performance portability metrics, as defined by Pennycook et al [1]. We believe this is the broadest and most rigorous performance portability study to date, representing a far reaching exploration of the state of performance portability that is achievable today. We will present a summary of the performance portability of each application and programming model across our diverge range of twelve computer architectures, including six different server CPUs from five different vendors, five different GPUs from two different vendors, and one vector architecture. We will conclude with an analysis of the performance portability of key programming models in general, across different application spaces as well across differing architectures, allowing us to comment on more general performance portability principles.