Combining Static and Dynamic Analysis to Query Characteristics of HPC Applications

Emerging HPC platforms are becoming more difficult to program as a result of systems with different node architectures, some with a small number of "fat" heterogenous nodes (consisting of multiple accelerators) and others with a large number of "thin" homogenous nodes consisting of multi-core CPUs connected with high speed interconnects. New programming models are emerging to address performance portability of the applications as well as a set of scientific libraries that applications can use to exploit these architectures efficiently. To port applications to new architectures, developers need information about their source code characteristics including static and dynamic (e.g. performance) information to refactor the code, understand their data and code structure, and library usage as well as program information to direct their optimisation efforts and make key decisions. In this paper, we describe a tool that combines compiler and profiler information to query program characteristics in a given programming environment. Static and dynamic data about applications is collected and stored together in an SQL database that can be later queried to study application characteristics and patterns. We will demonstrate the capabilities of this tool with an application-driven case study that aims at understanding application code and its use of scientific libraries via a real world example from the molecular simulation application CP2K.