Parallel programming model
From Wikipedia, the free encyclopedia
A parallel programming model is a set of software technologies to express parallel algorithms and match applications with the underlying parallel systems. It encloses the areas of applications, programming languages, compilers, libraries, communications systems, and parallel I/O. Due to the difficulties in automatic parallelization today, people have to choose a proper parallel programming model or a form of mixture of them to develop their parallel applications on a particular platform.
Parallel models are implemented in several ways: as libraries invoked from traditional sequential languages, as language extensions, or complete new execution models. They are also roughly categoried for two kinds of systems: shared-memory system and distributed-memory system, though the lines between them are largely blurred nowadays.
A programming model is usually judged by its expressibility and simplicity, which are by all meanings conflicting factors. The ultimate goal is to improve productivity of programming.
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[edit] Example parallel programming models
As of 2006, the current main-stream parallel programming models are:
- POSIX Threads
- PVM
- MPI
- OpenMP
- Global Arrays
- Co-Array Fortran
- UPC
- HPF
- SHMEM
- Stream processing
- Pipelining
Other research-level models are:
- Cray's Chapel,
- Sun’s Fortress,
- IBM’s X10
[edit] References
- H. Shan and J. Pal Singh. A comparison of MPI, SHMEM, and Cache-Coherent Shared Address Space Programming Models on a Tightly-Coupled Multiprocessor. International Journal of Parallel Programming, 29(3), 2001.
- H. Shan and J. Pal Singh. Comparison of Three Programming Models for Adaptive Applications on the Origin 2000. Journal of Parallel and Distributed Computing, 62:241–266, 2002.
- About structured parallel programming: Davide Pasetto and Marco Vanneschi. Machine independent Analytical models for cost evaluation of template--based programs, University of Pisa, 1996
