Parallel scheduling challenges raising at multiple levels of abstractions.- node level parallelism.- Minimization of energy consumption in task migration within a many-core chip;.- Task replication in real-time scheduling context.- Data-driven approach to schedule GPU load.- The use of lock-free data structures in OS scheduler.- The influence between user behaviour (think time, more precisely) and parallel scheduling.- Evalix, a predictor for job resource consumption.- Sophisticated and realistic simulation.- Space-filling curves leading to better scheduling of large-scale computers.- Discussion of real-life production experiences.
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