Scheduling and dispatching tools for High-Performance Computing (HPC) machines have the role of mapping incoming jobs to the available resources, trying to maximize equipment utilization and user satisfaction. Optimal Job Scheduling is a well-known NP-hard problem, forcing commercial schedulers to adopt greedy approaches based on rules. Constraint Programming (CP) is a well-known combinatorial optimization approach that has been shown to be very effective in optimally solving scheduling problems. We present the first CP-based job scheduler for HPC machines, working in a real-life production environment. We evaluate our solution both on a cluster of virtual machines and on the Eurora Supercomputer with production workloads. Results show significant improvements in terms of user fair-waiting without degradation in overall machine utilization w.r.t state-of-the-art rule-based dispatchers.

A CP scheduler for high-performance computers

BRIDI, THOMAS;LOMBARDI, MICHELE;BARTOLINI, ANDREA;BENINI, LUCA;MILANO, MICHELA
2015

Abstract

Scheduling and dispatching tools for High-Performance Computing (HPC) machines have the role of mapping incoming jobs to the available resources, trying to maximize equipment utilization and user satisfaction. Optimal Job Scheduling is a well-known NP-hard problem, forcing commercial schedulers to adopt greedy approaches based on rules. Constraint Programming (CP) is a well-known combinatorial optimization approach that has been shown to be very effective in optimally solving scheduling problems. We present the first CP-based job scheduler for HPC machines, working in a real-life production environment. We evaluate our solution both on a cluster of virtual machines and on the Eurora Supercomputer with production workloads. Results show significant improvements in terms of user fair-waiting without degradation in overall machine utilization w.r.t state-of-the-art rule-based dispatchers.
CEUR Workshop Proceedings
37
42
Bridi, Thomas; Lombardi, Michele; Bartolini, Andrea; Benini, Luca; Milano, Michela
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/585353
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