Automatic Performance Modeling and Analysis of Configurable Scientific Software and Workflows

Abstract

This work reduces the cost of automatic performance modeling and enables comparative analysis of workflow orchestration performance. We use parametric profiles to cut measurement costs, a method to identify performance-irrelevant options, and a serverless workflow benchmarking suite based on a Petri Net model. These contributions help developers and scientists better understand, model, and optimize application performance across diverse platforms and configurations.