Designing Efficient Parallel Software via Compositional Performance Modeling

Performance models are powerful instruments for understanding the performance of parallel systems and uncovering their bottlenecks. Already during system design, performance models can help ponder alternatives. However, creating a performance model - whether theoretically or empirically - for an entire application that does not exist yet is challenging unless the interactions between all system components are well understood, which is often not the case during design. In this paper, we propose to generate performance models of full programs from performance models of their components using formal composition operators derived from parallel design patterns such as pipeline or task pool. As long as the design of the overall system follows such a pattern, its performance model can be predicted with reasonable accuracy without an actual implementation.