Abstract
The increasing demand for computational resources, particularly in High-Performance Computing environments, necessitates to rethink how we handle job scheduling strategies. This work addresses the challenge of managing concurrent jobs with differing priorities on overloaded parallel systems, 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. This solution improves the response time for high-priority jobs by 50% without affecting the overall system utilization. We show its applicability in several critical scenarios such as High-Performance Computing (HPC) resource management and in-situ computing.
| Original language | English |
|---|---|
| Title of host publication | Euro-Par 2025 |
| Subtitle of host publication | Parallel Processing - 31st European Conference on Parallel and Distributed Processing, 2025, Proceedings |
| Editors | Wolfgang E. Nagel, Diana Goehringer, Pedro C. Diniz |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 219-232 |
| Number of pages | 14 |
| ISBN (Print) | 9783031998539 |
| DOIs | |
| State | Published - 2026 |
| Event | 31st European Conference on Parallel and Distributed Processing, Euro-Par 2025 - Dresden, Germany Duration: Apr 25 2025 → Apr 29 2025 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Volume | 15900 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 31st European Conference on Parallel and Distributed Processing, Euro-Par 2025 |
|---|---|
| Country/Territory | Germany |
| City | Dresden |
| Period | 04/25/25 → 04/29/25 |
Funding
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, for Research on Next Generation Data Management under Award Number DE-FOA-00002725. This work has benefited from a national grant managed by the French National Research Agency (Agence Nationale de la Recherche) attributed to the Exa-DoST project of the NumPEx PEPR program, under the reference ANR-22-EXNU-0004. This research uses data that was generated from resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. It used resources from Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.
Keywords
- Backfilling algorithm
- HPC
- Priority execution
- Scheduling