Hilbert curve scheduling: Difference between revisions

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[[File:Hilbert curve.png|thumb|Hilbert curves.]]

In [[Parallel computing|parallel processing]], the '''Hilbert curve scheduling''' method turns a multidimensional [[task scheduling|task allocation]] problem into a one -dimensional space filling problem using [[Hilbert curve]]s, assigning related tasks to locations with higher levels of proximity.<ref name=Hilbert>''Scheduling for Parallel Processing'' by Maciej Drozdowski 2009 {{ISBN 1848823096|1-84882-309-6}} page 166</ref> Other [[space filling curves]] may also be used in various computing applications for similar purposes.<ref name=HilbertEitan/>

The [[Simple Linux Utility for Resource Management|SLURM job scheduler]] which is used on a number of [[supercomputers]] uses a best fit algorithm based on Hilbert curve scheduling in order to optimize locality of task assignments.<ref name=Eitan>''Job Scheduling Strategies for Parallel Processing:'' by Eitan Frachtenberg and Uwe Schwiegelshohn 2010 {{ISBN 3642046320|3-642-04632-0}} pages 138-144</ref>

==See also==

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[[Category:ConcurrentJob computingscheduling]]

[[Category:Supercomputing]]