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A data-parallel model focuses on performing operations on a data set which is usually regularly structured in an array. A set of tasks will operate on this data, but independently on separate partitions. In a shared memory system, the data will be accessible to all, but in a distributed-memory system it will divided between memories and worked on locally. Data parallelism is usually classified as SIMD/SPMD.
 
====Idealised Parallel Systems====
 
The systems are categorized into 2 categories. The systems discussed in the first category were characterized by the isolation of the abstract design space seen by the programmer from the parallel, distributed implementation. In this, all processes are presented with equal access to some kind of shared memory space. In its loosest form, any process may attempt to access any item at any time.
The second category considers machines in which the two levels are closer together and in particular, those in which the programmers world includes explicit parallelism.This category discards shared memory based cooperation in favour of some form of explicit message passing.
 
== Example parallel programming models==
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* About [[structured parallel programming]]: Davide Pasetto and [[Marco Vanneschi]]. ''[http://portal.acm.org/citation.cfm?id=898142&coll=&dl=GUIDE&CFID=15151515&CFTOKEN=6184618 Machine independent Analytical models for cost evaluation of template--based programs]'', [[University of Pisa]], 1996
* {{Citation | author = J. Darlinton, M. Ghanem, H. W. To | year = 1993 | title = Structured Parallel Programming | journal =In Programming Models for Massively Parallel Computers. IEEE Computer Society Press. 1993 | url = http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.4610 }}
*Murray I. Cole. Algorithmic Skeletons:Structured Management of Parallel Computation
 
==External links ==