The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: 5th Workshop on Programming and Performance Visualization Tools (ProTools 2023)
Authors: Seyed Ali Mohammadi (Technical University of Darmstadt) and Lukas Rothenberger, Gustavo de Morais, Bertin Nico Görlich, Erik Lille, Hendrik Rüthers, and Felix Wolf (Technical University Darmstadt)
Abstract: Many high-performance computing applications reach millions of code lines and hundreds of code regions. Analyzing all code regions for parallelization with OpenMP is neither efficient nor necessary. To facilitate this task and minimize the effort by the user, the code regions of the application need to be filtered and ranked. We provide a simple filtering method to detect the critical code regions by clearly defining a hotspot. Afterward, we identify parallelizable loops by analyzing their data dependencies using an automatic tool. As the number of parallel opportunities can be high and the users must verify these parallel suggestions, we suggest a ranking strategy based on parallelization overhead to help them prioritize their endeavors and present a set of OpenMP microbenchmarks for overhead analysis. We calculate optimistic expected benefits using overhead estimations as ranking metrics and show how our ranking provides an improvement on the ranking based on serial runtime.