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Constraint Programming (CP) is a well-established area in AI as a programmingparadigm for modelling and solving discrete optimization problems, and it hasbeen been successfully applied to tackle the on-line job dispatching problem inHPC systems including those running modern applications. The limitations of theavailable CP-based job dispatchers may hinder their practical use in today'ssystems that are becoming larger in size and more demanding in resourceallocation. In an attempt to bring basic AI research closer to a deployedapplication, we present a new CP-based on-line job dispatcher for modern HPCsystems and applications. Unlike its predecessors, our new dispatcher tacklesthe entire problem in CP and its model size is independent of the system size.Experimental results based on a simulation study show that with our approachdispatching performance increases significantly in a large system and in asystem where allocation is nontrivial.

A Constraint Programming-based Job Dispatcher for Modern HPC Systems and Applications