Reshaping Analysis for Fast Turnaround: Leveraging Concurrency to Reduce Latency in Late-Stage LHC Analysis Workflows

¹ Department of Physics and Astronomy, University of Notre Dame, Notre Dame, IN, 46530, USA
² Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46530, USA
³ Center for Research Computing, University of Notre Dame, Notre Dame, IN, 46530, USA

^* e-mail: klannon@nd.edu

Published online: 7 October 2025

Abstract

In the data analysis pipeline for LHC experiments, a key aspect is the step in which particle-level data is reduce to summary statistics allowing insights to be extracted through statistical analysis. Here, we will refer to this step as “analysis.” Analysis is a very important part of the pipeline as it is the step where individual researchers exercise their creativity in trying new ideas in the pursuit of discovery. Therefore, a critical metric for the analysis step is turnaround time because it determines how rapidly researchers can explore their space of ideas. We demonstrate our experience reshaping latestage analysis applications on thousands of nodes with the goal of minimizing turnaround time. It is not enough merely to increase scale: it is necessary to make changes throughout the stack, including storage systems, data management, task scheduling, and application design.