About: Automatic parallelization tool

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For several years parallel hardware was only available for distributed computing but recently it is becoming available for the low end computers as well. Hence it has become inevitable for software programmers to start writing parallel applications. It is quite natural for programmers to think sequentially and hence they are less acquainted with writing multi-threaded or parallel processing applications. Parallel programming requires handling various issues such as synchronization and deadlock avoidance. Programmers require added expertise for writing such applications apart from their expertise in the application domain. Hence programmers prefer to write sequential code and most of the popular programming languages support it. This allows them to concentrate more on the application. There

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rdfs:label	Automatic parallelization tool (en)
rdfs:comment	For several years parallel hardware was only available for distributed computing but recently it is becoming available for the low end computers as well. Hence it has become inevitable for software programmers to start writing parallel applications. It is quite natural for programmers to think sequentially and hence they are less acquainted with writing multi-threaded or parallel processing applications. Parallel programming requires handling various issues such as synchronization and deadlock avoidance. Programmers require added expertise for writing such applications apart from their expertise in the application domain. Hence programmers prefer to write sequential code and most of the popular programming languages support it. This allows them to concentrate more on the application. There (en)
sameAs	Automatic parallelization tool
dbp:wikiPageUsesTemplate	dbt:Refimprove dbt:Reflist dbt:Outdated
Subject	Parallel computing
Link from a Wikipage to an external page	http://www.emmtrix.com/tools/emmtrix-parallel-studio http://www.par4all.org/features http://cetus.ecn.purdue.edu http://pluto-compiler.sourceforge.net http://traco.sourceforge.net http://traco.sourceforge.net. https://en.wikibooks.org/wiki/ROSE_Compiler_Framework/autoPar https://github.com/claw-project/claw-compiler https://github.com/sdruix/OMP2HMPP https://github.com/sdruix/OMP2MPI https://web.archive.org/web/20141219215942/http:/www.timing-architects.com/ta-tool-suite/optimizer.html https://software.intel.com/en-us/intel-advisor-xe
thumbnail	wiki-commons:Special:FilePath/ROSE-autoPar-workflow.png?width=300
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Link from a Wikipage to another Wikipage	Fortran Privatization Supercomputer Analyser Automatic parallelization Binary Modular Dataflow Machine SequenceL Thread (computing) C++ CUDA C (programming language) Parallel computing Distributed computing Java (programming language) Message Passing Interface NanoHUB Client–server model Deadlock KPIT Technologies Pthreads Purdue University Runtime (program lifecycle phase) Source-to-source compiler Compile time OpenMP Optimizing compiler Parallel computing SPMD Speedup Data dependency Computer graphics Graphics processing unit Scalable parallelism Scheduling (computing) Scilab Synchronization Induction variable Intel C++ Compiler Stanford University Loop nest optimization Lexical analysis MATLAB Polytope model Simulink dbr:Cetus_Source-to-source_Translation_Framework dbr:HMPP
has abstract	For several years parallel hardware was only available for distributed computing but recently it is becoming available for the low end computers as well. Hence it has become inevitable for software programmers to start writing parallel applications. It is quite natural for programmers to think sequentially and hence they are less acquainted with writing multi-threaded or parallel processing applications. Parallel programming requires handling various issues such as synchronization and deadlock avoidance. Programmers require added expertise for writing such applications apart from their expertise in the application domain. Hence programmers prefer to write sequential code and most of the popular programming languages support it. This allows them to concentrate more on the application. Therefore, there is a need to convert such sequential applications to parallel applications with the help of automated tools. The need is also non-trivial because large amount of legacy code written over the past few decades needs to be reused and parallelized. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Automatic_parallelization_tool
is rdfs:seeAlso of	Automatic parallelization
is Wikipage redirect of	OMP2MPI Automatic parallelisation tool List of automatic parallelisation tools List of automatic parallelization tools SUIF Par4All Polaris compiler
is Link from a Wikipage to another Wikipage of	OMP2MPI Automatic parallelisation tool Automatic parallelization List of automatic parallelisation tools List of automatic parallelization tools
is foaf:primaryTopic of	http://en.wikipedia.org/wiki/Automatic_parallelization_tool

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