Hilbert curve scheduling: Difference between revisions

Revision as of 17:31, 27 February 2012

Latest revision as of 18:40, 13 February 2024

(7 intermediate revisions by 6 users not shown)

Line 1:

[[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==

Line 12 ⟶ 13:

{{Comp-eng-stub}}

[[Category:ConcurrentJob computingscheduling]]

[[Category:Supercomputing]]