My talk for the 18th scheduling workshop workshop focuses on efficiently executing the analysis codes attached to large-scale simulations. These tasks require the data generated at every simulation step in order to extract knowledge (quantities or regions of interest), post-process data for training, to reduce or refactor parts of the data or simply visualize and audit the data.

The increasing demand for computational resources, particularly for these analysis tasks attached to HPC simulations, necessitates to re-think how we handle job scheduling strategies. My talk addresses the challenge of managing concurrent jobs with differing priorities on limited compute resources and within a fixed time window and where strict QoS constraints are often difficult for users to define. Our solution relies on a qualitative description of priorities and pulls from two key approaches: the Easy-BF algorithm and the Conservative Backfilling algorithms.

Link to the event: 18th Scheduling for large-scale systems workshop Website
Link to my talk: PDF

This talk is based on the paper:
Priority-BF: a Task Manager for Priority-Based Scheduling
Ana Gainaru, Scott Klasky, Guillaume Pallez
EURO-PAR 2025-31st International European Conference on Parallel and Distributed Computing, 2025