- By:
- Eiffert, Brett C; Zhang, Chen
- Page Number:
- 329-344
- Volume:
- 1690
- Issue Number:
- CCIS
- Book Title:
- Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation
- Publication Date:
- November 9, 2023
- Publisher Location:
- Springer, Cham, Switzerland
- Conference Name:
- Smoky Mountains Computational Sciences and Engineering Conference 2022 (SMC)
- Conference Location:
- Remote, Tennessee, United States of America
- Conference Sponsor:
- Oak Ridge National Laboratory
- View DOI Listing:
- https://doi.org/10.1007/978-3-031-23606-8_21
Abstract
High performance computing (HPC) users interact with Summit through dedicated gateways, also known as login nodes. The performance and stability of these login nodes can have a significant impact on the user experience. In this study, the performance and stability of Summit’s five login nodes are evaluated by analyzing the log data from 2020 and 2021. The analysis focuses on the computing capability (CPU average load, users and tasks) and the storage performance, along with the associated job scheduler activity. The outcome of this study can serve as the foundation of a predictive modeling framework that enables the system admin of an HPC system to preemptively deploy countermeasures before the onset of a system failure.
