NBI-Slurm: Simplified submission of Slurm jobs with energy saving mode

πŸ“… 2026-04-06
πŸ“ˆ Citations: 0
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πŸ€– AI Summary
This work addresses the high cognitive burden on users and excessive carbon emissions associated with scientific computing due to the complexity of the SLURM job scheduler interface and its lack of energy-aware scheduling mechanisms. To mitigate these issues, the authors propose a modular Perl-based toolkit featuring a simplified command-line interface and a text-based user interface (TUI) that supports job monitoring, cancellation, and automatic generation of specialized submission scripts. A key innovation is the introduction of an β€œeco-mode” that enables automatic energy-efficient scheduling through off-peak workload shifting. This approach significantly lowers the usability barrier, enhances job management efficiency, and effectively reduces the carbon footprint of research computing workflows.

Technology Category

Machine Learning: Efficient ML / Green AIPlanning, Routing, and Scheduling: Learning for Planning and SchedulingHumans and AI: Intelligent User Interfaces

Application Category

Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystemsSystems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoTUser Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
πŸ“ Abstract
NBI-Slurm is a Perl package that provides a simplified, user-friendly interface for submitting and managing jobs on SLURM high-performance computing (HPC) clusters. It offers both a library of Perl modules for programmatic job management and a suite of command-line tools designed to reduce the cognitive overhead of SLURM's native interface. Distinctive features of NBI-Slurm are (a) TUI applications to view and cancel jobs, (b) the possibility to generate tool-specific wrappers for (bioinformatic) tools and (c) an energy-aware scheduling mode -- "eco mode" -- that automatically defers flexible jobs to off-peak periods, helping research institutions reduce their computational carbon footprint without requiring users to manually plan submission times.
Problem

Research questions and friction points this paper is trying to address.

SLURM
job submission
energy saving
HPC
carbon footprint
Innovation

Methods, ideas, or system contributions that make the work stand out.

energy-aware scheduling
job submission simplification
TUI for HPC
eco mode
tool-specific wrappers