Interpreting and Visualizing Performance Portability Metrics

Recent work has introduced a number of tools and techniques for reasoning about the interplay between application performance and portability, or "performance portability". These tools have proven useful for setting goals and guiding high-level discussions, but our understanding of the performance portability problem remains incomplete. Different views of the same performance efficiency data offer different insights into an application's performance portability (or lack thereof): standard statistical measures such as the mean and standard deviation require careful interpretation, and even metrics designed specifically to measure performance portability may obscure differences between applications.This paper offers a critical assessment of existing approaches for summarizing performance efficiency data across different platforms, and proposes visualization as a means to extract useful information about the underlying distribution. We explore a number of alternative visualizations, outlining a new methodology that enables developers to reason about the performance portability of their applications and how it might be improved. This study unpicks what it might mean to be "performance portable" and provides useful tools to explore that question.