Scalable HPC Job Scheduling and Resource Management in SST
Efficient job scheduling and resource management contributes towards system throughput and efficiency maximization in high-performance computing (HPC) systems. In this paper, we introduce a scalable job scheduling and resource management component within the structural simulation toolkit (SST), a cycle-accurate and parallel discrete-event simulator. Our proposed simulator includes state-of-the-art job scheduling algorithms and resource management techniques. Additionally, it introduces a workflow management components that supports the simulation of task dependencies and resource allocations, crucial for workflows typical in scientific computing and data-intensive applications. We present validation and scalability results of our job scheduling simulator. Simulation shows that our simulator achieves good accuracy in various metrics (e.g., job wait times, number of nodes usage) and also achieves good parallel performance.
Authors
- Kishwar Ahmed
- Kazutomo Yoshii (ORCID: https://orcid.org/0000-0003-1904-5383)
- Kevin A. Brown (ORCID: https://orcid.org/0000-0002-0935-5743)
- Abrar Hossain
- Abubeker Abdurahman
Institutions
- Argonne National Laboratory (US)
- University of Toledo (US)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/wsc63780.2024.10838714
- Citations
- 4
- Primary Topic
- Distributed and Parallel Computing Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.40
Funders
- National Science Foundation
- U.S. Department of Energy
- Office of Science