Toward Automated Application Profiling on Cray Systems

Application performance data can be used by HPC users to optimize their code and prioritize their development efforts, and by HPC facilities to better understand their user base and guide their future procurements. This paper presents an exploration of six commonly used profiling tools in order to assess their ability to enable automated passive performance data collection on Cray systems. Each tool is benchmarked with three applications with distinct performance characteristics, to collect five pre-selected metrics such as the total number of floating-point operations and memory bandwidth. Results are then used to evaluate the tools’ usability, overhead to run, amount of actionable information that they can provide, and accuracy of the information provided. Keywords-automated profiling; performance tools; Cray; HPC;