Streamlining Performance Analysis Workflows Using Compiler-Assisted Instrumentation Selection

Efficient performance analysis is crucial for optimizing scientific applications. The traditional instrumentation workflow may require multiple manual refinements of the instrumentation configuration to minimize measurement perturbations, which can be time-consuming. This paper presents two approaches to streamline these workflows, guided by a compiler-generated static whole-program call graph of the target application. The Compiler-assisted Performance Instrumentation tool (CaPI) enables the user to build modular selection pipelines, which can be tailored to the application and measurement objective. Performance Instrumentation Refinement Automation (PIRA) combines static call graph analysis with dynamic profiling for iterative refinement. Ongoing work aims to integrate these approaches into a unified production tool, emphasizing workflow efficiency.