Introducing and Exploiting Hierarchical Structural Information

This paper presents a programming model approach that explicitly addresses the programmability of scientific code by annotating imperative code with its algorithmic structural behavior. This information is used to create hierarchical structures, as opposed to the flat structure that most programming models work with, which allows sound code transformation at any level of the code, adjusting the granularity of parallelization simultaneously with other parameters to better exploit the available hardware resources.