A machine learning framework for performance coverage analysis of proxy applications

Proxy applications are written to represent subsets of performance behaviors of larger, and more complex applications that often have distribution restrictions. They enable easy evaluation of these behaviors across systems, e.g., for procurement or co-design purposes. However, the intended correlation between the performance behaviors of proxy applications and their parent codes is often based solely on the developer's intuition. In this paper,...