Scalable HPC Job Scheduling and Resource Management in SST

Fuente: arXiv
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Auteurs principaux: Abdurahman, Abubeker, Hossain, Abrar, Brown, Kevin A, Yoshii, Kazutomo, Ahmed, Kishwar
Format: Preprint
Publié: 2025
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author Abdurahman, Abubeker
Hossain, Abrar
Brown, Kevin A
Yoshii, Kazutomo
Ahmed, Kishwar
author_facet Abdurahman, Abubeker
Hossain, Abrar
Brown, Kevin A
Yoshii, Kazutomo
Ahmed, Kishwar
contents Efficient job scheduling and resource management contribute 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 workflow management components that support the simulation of task dependencies and resource allocations, crucial for workflows typical in scientific computing and data-intensive applications. We present the 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.
format Preprint
id arxiv_https___arxiv_org_abs_2501_18191
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Scalable HPC Job Scheduling and Resource Management in SST
Abdurahman, Abubeker
Hossain, Abrar
Brown, Kevin A
Yoshii, Kazutomo
Ahmed, Kishwar
Distributed, Parallel, and Cluster Computing
Efficient job scheduling and resource management contribute 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 workflow management components that support the simulation of task dependencies and resource allocations, crucial for workflows typical in scientific computing and data-intensive applications. We present the 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.
title Scalable HPC Job Scheduling and Resource Management in SST
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2501.18191