Computer cluster: Difference between revisions

Revision as of 15:13, 21 May 2022

Revision as of 16:58, 28 June 2022

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Computer clustering relies on a centralized management approach which makes the nodes available as orchestrated shared servers. It is distinct from other approaches such as [[peer-to-peer]] or [[grid computing]] which also use many nodes, but with a far more [[distributed computing|distributed nature]].<ref name=nbis />

A computer cluster may be a simple two-node system which just connects two personal computers, or may be a very fast [[supercomputer]]. A basic approach to building a cluster is that of a [[Beowulf (computing)|Beowulf]] cluster which may be built with a few personal computers to produce a cost-effective alternative to traditional [[high -performance computing]]. An early project that showed the viability of the concept was the 133-node [[Stone Soupercomputer]].<ref name="sciam">{{Cite news |title= The Do-It-Yourself Supercomputer |work= [[Scientific American]] |author= William W. Hargrove, Forrest M. Hoffman and [[Thomas Sterling (computing)|Thomas Sterling]] |volume= 265 |number= 2 |pages= 72–79 |date= August 16, 2001 |url= http://www.sciam.com/article.cfm?id=the-do-it-yourself-superc |access-date= October 18, 2011 }}</ref> The developers used [[Linux]], the [[Parallel Virtual Machine]] toolkit and the [[Message Passing Interface]] library to achieve high performance at a relatively low cost.<ref name="extreme">{{Cite news |title= Cluster Computing: Linux Taken to the Extreme |first1= William W. |last1= Hargrove |first2= Forrest M. |last2= Hoffman |work= Linux Magazine |year= 1999 |url= http://climate.ornl.gov/~forrest/linux-magazine-1999/ |access-date= October 18, 2011 |archive-url= https://web.archive.org/web/20111018122713/http://climate.ornl.gov/~forrest/linux-magazine-1999/ |archive-date= October 18, 2011 |url-status= dead }}</ref>

Although a cluster may consist of just a few personal computers connected by a simple network, the cluster architecture may also be used to achieve very high levels of performance. The [[TOP500]] organization's semiannual list of the 500 fastest [[supercomputer]]s often includes many clusters, e.g. the world's fastest machine in 2011 was the [[K computer]] which has a [[distributed memory]], cluster architecture.<ref>{{cite conference|first=Mitsuo|last=Yokokawa |display-authors=etal |title=The K computer: Japanese next-generation supercomputer development project|conference=International Symposium on Low Power Electronics and Design (ISLPED)|date=1–3 August 2011|pages=371–372|doi=10.1109/ISLPED.2011.5993668}}</ref>

== History ==

{{Main|History of computer clusters}}

{{See also|History of supercomputing}}

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==Benefits==

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Clusters are primarily designed with performance in mind, but installations are based on many other factors. Fault tolerance (''the ability for a system to continue working with a malfunctioning node'') allows for [[horizontal scaling|scalability]], and in high -performance situations, low frequency of maintenance routines, resource consolidation (e.g. [[RAID]]), and centralized management. Advantages include enabling data recovery in the event of a disaster and providing parallel data processing and high processing capacity.<ref>{{cite web|url=http://www-03.ibm.com/systems/clusters/benefits.html|title=IBM Cluster System : Benefits|publisher=[[IBM]]|access-date=8 September 2014|archive-url=https://web.archive.org/web/20160429022854/http://www-03.ibm.com/systems/clusters/benefits.html|archive-date=29 April 2016|url-status=dead}}</ref><ref>{{cite web|url=https://technet.microsoft.com/en-us/library/cc778629(v=ws.10).aspx|title=Evaluating the Benefits of Clustering|date=28 March 2003|publisher=[[Microsoft]]|access-date=8 September 2014|archive-url=https://web.archive.org/web/20160422092651/https://technet.microsoft.com/en-us/library/cc778629%28v%3Dws.10%29.aspx|archive-date=22 April 2016|url-status=dead}}</ref>

In terms of scalability, clusters provide this in their ability to add nodes horizontally. This means that more computers may be added to the cluster, to improve its performance, redundancy and fault tolerance. This can be an inexpensive solution for a higher performing cluster compared to scaling up a single node in the cluster. This property of computer clusters can allow for larger computational loads to be executed by a larger number of lower performing computers.

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The Linux world supports various cluster software; for application clustering, there is [[distcc]], and [[MPICH]]. [[Linux Virtual Server]], [[Linux-HA]] - director-based clusters that allow incoming requests for services to be distributed across multiple cluster nodes. [[MOSIX]], [[LinuxPMI]], [[Kerrighed]], [[OpenSSI]] are full-blown clusters integrated into the [[kernel (computer science)|kernel]] that provide for automatic process migration among homogeneous nodes. [[OpenSSI]], [[openMosix]] and [[Kerrighed]] are [[single-system image]] implementations.

[[Microsoft Windows]] computer cluster Server 2003 based on the [[Windows Server]] platform provides pieces for High -Performance Computing like the Job Scheduler, MSMPI library and management tools.

[[gLite]] is a set of middleware technologies created by the [[Enabling Grids for E-sciencE]] (EGEE) project.

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Although most computer clusters are permanent fixtures, attempts at [[flash mob computing]] have been made to build short-lived clusters for specific computations. However, larger-scale [[volunteer computing]] systems such as [[BOINC]]-based systems have had more followers.

== See also ==

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== References ==

{{Reflist|30em}}

== Further reading ==

* {{cite arXiv|first=Mark|last=Baker |display-authors=etal |title=Cluster Computing White Paper|eprint=cs/0004014|date=11 Jan 2001}}

* {{cite book|first1=Evan|last1=Marcus|first2=Hal|last2=Stern|title=Blueprints for High Availability: Designing Resilient Distributed Systems|publisher=John Wiley & Sons|isbn=978-0-471-35601-1|date=2000-02-14|url=https://archive.org/details/blueprintsforhig00marc}}

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* {{cite book|editor-first=Rajkumar|editor-last=Buyya|title=High Performance Cluster Computing: Architectures and Systems|volume=2|isbn=978-0-13-013785-2|publisher=Prentice Hall|___location=NJ, USA|year=1999}}

== External links ==

{{Commons category|Clusters (computing)}}

* [https://web.archive.org/web/20190219183441/https://www.ieeetcsc.org/ IEEE Technical Committee on Scalable Computing (TCSC)]