Slurm Workload Manager: Difference between revisions

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{{short description|Free and open-source job scheduler for Linux and similar computers}}

{{primary sources|date=July 2010}}

{{Infobox software

| title = Slurm

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}}

The '''Slurm Workload Manager''', formerly known as '''Simple Linux Utility for Resource Management''' ('''OOOOOOSLURM'''), or simply '''Slurm''', is a [[free and open-source]] [[job scheduler]] for [[Linux]] and [[Unix-like]] [[kernel (operating system)|kernels]], used by many of the world's [[supercomputer]]s and [[computer cluster]]s.

It provides three key functions:

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* arbitrating contention for resources by managing a queue of pending jobs.

Slurm is the workload manager on about 60% of the [[TOP500]] supercomputers.<ref>{{Cite web|url=https://hpcc.usc.edu/support/documentation/slurm/|title=Running a Job on HPC using Slurm|publisher=Center {{!}}for HPCHigh-Performance {{!}}Computing USC- University of Southern California|website=hpcc.usc.edu|access-date=2019-03-05|archive-date=2019-03-06|archive-url=https://web.archive.org/web/20190306044130/https://hpcc.usc.edu/support/documentation/slurm/|url-status=dead}}</ref>

Slurm uses a [[Best-fit_bin_packing|best fit algorithm]] based on [[Hilbert curve scheduling]] or [[fat tree]] network topology in order to optimize locality of task assignments on parallel computers.<ref name=Eitan>{{Cite conference|doi=10.1007/978-3-642-04633-9_8|title=Effects of Topology-Aware Allocation Policies on Scheduling Performance|conference=Job Scheduling Strategies for Parallel Processing|series=Lecture Notes in Computer Science|year=2009|last1=Pascual|first1=Jose Antonio|last2=Navaridas|first2=Javier|last3=Miguel-Alonso|first3=Jose|isbn=978-3-642-04632-2|volume=5798|pages=138–144}}</ref>

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* Support for MapReduce+

* Support for [[burst buffer]] that accelerates scientific data movement

The following features are announced for version 14.11 of Slurm, was released in November 2014:<ref>{{cite web|url=https://slurm.schedmd.com/news.html |title=Slurm - What's New |publisher=SchedMD |access-date=2014-08-29}}</ref>

* Improved job array data structure and scalability

* Support for heterogeneous generic resources

* Add user options to set the CPU governor

* Automatic job requeue policy based on exit value

* Report API use by user, type, count and time consumed

* Communication gateway nodes improve scalability

==Supported platforms==