Massively parallel

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In computing, massively parallel refers to the use of a large number of processors (or separate computers) to perform a set of coordinated computations in parallel (simultaneously).


In one approach, e.g., in grid computing the processing power of a large number of computers in distributed, diverse administrative domains, is opportunistically used whenever a computer is available.[1] An example is BOINC, a volunteer-based, opportunistic grid system, whereby the grid provides power only on a best effort basis.[2]


In another approach, a large number of processors are used in close proximity to each other, e.g., in a computer cluster. In such a centralized system the speed and flexibility of the interconnect becomes very important, and modern supercomputers have used various approaches ranging from enhanced Infiniband systems to three-dimensional torus interconnects.[3]


The term also applies to massively parallel processor arrays (MPPAs), a type of integrated circuit with an array of hundreds or thousands of central processing units (CPUs) and random-access memory (RAM) banks. These processors pass work to one another through a reconfigurable interconnect of channels. By harnessing a large number of processors working in parallel, an MPPA chip can accomplish more demanding tasks than conventional chips.[citation needed] MPPAs are based on a software parallel programming model for developing high-performance embedded system applications.


Goodyear MPP was an early implementation of a massively parallel computer architecture. MPP architectures are the second most common supercomputer implementations after clusters, as of November 2013.[4]


Data warehouse appliances such as Teradata, Netezza or Microsoft's PDW commonly implement an MPP architecture to handle the processing of very large amounts of data in parallel.



See also


  • Multiprocessing

  • Embarrassingly parallel

  • Parallel computing

  • Process-oriented programming


  • Shared-nothing architecture (SN)


  • Symmetric multiprocessing (SMP)

  • Connection Machine

  • Cellular automaton

  • CUDA framework

  • Manycore processor

  • Vector processor


References




  1. ^ Grid computing: experiment management, tool integration, and scientific workflows by Radu Prodan, Thomas Fahringer 2007 .mw-parser-output cite.citationfont-style:inherit.mw-parser-output .citation qquotes:"""""""'""'".mw-parser-output .citation .cs1-lock-free abackground:url("//upload.wikimedia.org/wikipedia/commons/thumb/6/65/Lock-green.svg/9px-Lock-green.svg.png")no-repeat;background-position:right .1em center.mw-parser-output .citation .cs1-lock-limited a,.mw-parser-output .citation .cs1-lock-registration abackground:url("//upload.wikimedia.org/wikipedia/commons/thumb/d/d6/Lock-gray-alt-2.svg/9px-Lock-gray-alt-2.svg.png")no-repeat;background-position:right .1em center.mw-parser-output .citation .cs1-lock-subscription abackground:url("//upload.wikimedia.org/wikipedia/commons/thumb/a/aa/Lock-red-alt-2.svg/9px-Lock-red-alt-2.svg.png")no-repeat;background-position:right .1em center.mw-parser-output .cs1-subscription,.mw-parser-output .cs1-registrationcolor:#555.mw-parser-output .cs1-subscription span,.mw-parser-output .cs1-registration spanborder-bottom:1px dotted;cursor:help.mw-parser-output .cs1-ws-icon abackground:url("//upload.wikimedia.org/wikipedia/commons/thumb/4/4c/Wikisource-logo.svg/12px-Wikisource-logo.svg.png")no-repeat;background-position:right .1em center.mw-parser-output code.cs1-codecolor:inherit;background:inherit;border:inherit;padding:inherit.mw-parser-output .cs1-hidden-errordisplay:none;font-size:100%.mw-parser-output .cs1-visible-errorfont-size:100%.mw-parser-output .cs1-maintdisplay:none;color:#33aa33;margin-left:0.3em.mw-parser-output .cs1-subscription,.mw-parser-output .cs1-registration,.mw-parser-output .cs1-formatfont-size:95%.mw-parser-output .cs1-kern-left,.mw-parser-output .cs1-kern-wl-leftpadding-left:0.2em.mw-parser-output .cs1-kern-right,.mw-parser-output .cs1-kern-wl-rightpadding-right:0.2em
    ISBN 3-540-69261-4 pages 1–4



  2. ^ Parallel and Distributed Computational Intelligence by Francisco Fernández de Vega 2010
    ISBN 3-642-10674-9 pages 65–68



  3. ^ Knight, Will: "IBM creates world's most powerful computer", NewScientist.com news service, June 2007


  4. ^ http://s.top500.org/static/lists/2013/11/TOP500_201311_Poster.png









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