A Formally Verified AI Framework for Scheduling OptimiSation in Slurm-Based Distributed HPC Systems
This paper presents an artificial intelligence (AI)-enabled scheduling framework for Slurm that integrates formal verification techniques with data-driven optimization methods. The proposed architecture combines concepts from queueing theory, Markov chain modeling, graph theory, mathematical optimization, reinforcement...