You do not have permission to edit this page, for the following reasons:

This IP address has been blocked from editing Wikipedia.
This does not affect your ability to read Wikipedia pages.
Most people who see this message have done nothing wrong. Some kinds of blocks restrict editing from specific service providers or telecom companies in response to recent abuse or vandalism, and can sometimes affect other users who are unrelated to that abuse. Review the information below for assistance if you do not believe that you have done anything wrong.

The IP address or range 18.208.0.0/16 has been blocked (disabled) by ‪ST47‬ for the following reason(s):

The IP address that you are currently using has been blocked because it is believed to be a web host provider. To prevent abuse, web hosts may be blocked from editing Wikipedia.
You will not be able to edit Wikipedia using a web host provider because it hides your IP address, much like a proxy or VPN.
We recommend that you attempt to use another connection to edit. For example, if you use a proxy or VPN to connect to the internet, turn it off when editing Wikipedia. If you edit using a mobile connection, try using a Wi-Fi connection, and vice versa. If you are using a corporate internet connection, switch to a different Wi-Fi network. If you have a Wikipedia account, please log in.
If you do not have any other way to edit Wikipedia, you will need to request an IP block exemption.

How to appeal if you are confident that your connection does not use a web host's IP address:
If you are confident that you are not using a web host, you may appeal this block by adding the following text on your talk page: ((unblock|reason=Caught by a web host block but this host or IP is not a web host. My IP address is _______. Place any further information here. ~~~~)). You must fill in the blank with your IP address for this block to be investigated. Your IP address can be determined here. Alternatively, if you wish to keep your IP address private you can use the unblock ticket request system. There are several reasons you might be editing using the IP address of a web host (such as if you are using VPN software or a business network); please use this method of appeal only if you think your IP address is in fact not a web host.

Administrators: The IP block exemption user right should only be applied to allow users to edit using web host in exceptional circumstances, and they should usually be directed to the functionaries team via email. If you intend to give the IPBE user right, a CheckUser needs to take a look at the account. This can be requested most easily at SPI Quick Checkuser Requests. Unblocking an IP or IP range with this template is highly discouraged without at least contacting the blocking administrator.

This block will expire on 01:01, 24 April 2026.

Even when blocked, you will usually still be able to edit your user talk page, as well as email administrators and other editors.

For information on how to proceed, please read the FAQ for blocked users and the guideline on block appeals. The guide to appealing blocks may also be helpful.

Other useful links: Blocking policy · Help:I have been blocked
Your IP address is in a range that has been blocked on all Wikimedia Foundation wikis. The block was made by ‪AntiCompositeNumber‬. The reason given is Open proxy/Webhost: See the help page if you are affected .
- Start of block: 15:08, 30 August 2023
- Expiry of block: 15:08, 30 August 2025
Your current IP address is 18.208.109.86. The blocked range is 18.208.0.0/16. Please include all above details in any queries you make. If you believe you were blocked by mistake, you can find additional information and instructions in the No open proxies global policy. Otherwise, to discuss the block please post a request for review on Meta-Wiki. You could also send an email to the stewards VRT queue at stewards@wikimedia.org including all above details.

You can view and copy the source of this page:

((Short description | Tool for converting sequential code to parallel))((outdated|date=September 2019))
((refimprove |date=May 2011))

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 computing|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.

==Need for automatic parallelization==

Past  techniques provided solutions for languages like FORTRAN and C; however, these are not enough. These techniques dealt with parallelization sections with specific system in mind like loop or particular section of code. Identifying opportunities for parallelization is a critical step while generating multithreaded application. This need to parallelize applications is partially addressed by tools that analyze code to exploit parallelism. These tools use either [[compile time]] techniques or [[Run time (program lifecycle phase)|run-time]] techniques.  These techniques are built-in in some parallelizing compilers but user needs to identify parallelize code and mark the code with special language constructs. The compiler identifies these language constructs and analyzes the marked code for parallelization. Some tools parallelize only special form of code like loops. Hence a fully automatic tool for converting sequential code to parallel code is required.<ref>“Increasing Parallelism on Multicore Processors Using Induced Parallelism”, by Vinay G. Vaidya, PushpRaj Agrawal, Aditi Athavale, Anish Sane, Sudhakar Sah and Priti Ranadive</ref>

==General procedure of parallelization==

1. The process starts with identifying code sections that the programmer feels have parallelism possibilities. Often this task is difficult
since the programmer who wants to parallelize the code has not originally written the code under consideration. Another possibility is that
the programmer is new to the application domain. Thus, though this first stage in the parallelization process seems easy at first it may
not be so.

2. The next stage is to shortlist code sections out of the identified ones that are actually parallelization. This stage is again most
important and difficult since it involves lot of analysis. Generally for codes in [[C (programming language)|C]]/[[C++]] where pointers are involved are difficult to
analyze. Many special techniques such as pointer alias analysis, functions side effects analysis are required to conclude whether a section
of code is dependent on any other code. If the dependencies in the identified code sections are more the possibilities of parallelization
decreases.

3. Sometimes the dependencies are removed by changing the code and this is the next stage in parallelization. Code is transformed such that
the functionality and hence the output is not changed but the dependency, if any, on other code section or other instruction is removed.

4. The last stage in parallelization is generating the parallel code. This code is always functionally similar to the original sequential code
but has additional constructs or code sections which when executed create multiple threads or processes.

==Automatic parallelization technique==
See also main article [[automatic parallelization]].
===Scan===
This is the first stage where the scanner will read the input source files to identify all static and extern usages. Each line in the file will be checked against pre-defined patterns to segregate into [[token (parser)|token]]s. These tokens will be stored in a file which will be used later by the
grammar engine. The grammar engine will check patterns of tokens that match with pre-defined rules to identify variables, loops, controls
statements, functions etc. in the code.....

===Analyze===
The [[analyzer]] is used to identify sections of code that can be executed concurrently. The analyzer uses the static data information provided by the scanner-parser. The analyzer will first find out all the functions that are totally independent of each other and mark them as
individual tasks. Then analyzer finds which tasks are having dependencies.

===Schedule===
The [[Scheduling (computing)|scheduler]] will lists all the tasks and their dependencies on each other in terms of execution and start times. The scheduler will produce optimal schedule in terms of number of processors to be used or the total time of execution for the application.

===Code Generation===
The [[Scheduling (computing)|scheduler]] will generate list of all the tasks and the details of the cores on which they will execute along with the time that they
will execute for. The code Generator will insert special constructs in the code that will be read during execution by the scheduler. These
constructs will instruct the scheduler on which core a particular task will execute along with the start and end times......

==Parallelization tools==

There are a number of Automatic Parallelization tools for Fortran, C, C++, and several other languages.

===YUCCA===

YUCCA is a Sequential to Parallel automatic code conversion tool developed by [[KPIT Technologies]] Ltd. Pune. It takes input as C source code which may have multiple source and header files. It gives output as transformed [[multi-threaded]] parallel code using [[pthreads]] functions and [[OpenMP]] constructs. The YUCCA tool does task and loop level parallelization.

===Par4All===

Par4All is an automatic parallelizing and [[optimizing compiler]] (workbench) for C and Fortran sequential programs. The purpose of this
[[source-to-source compiler]] is to adapt existing applications to various hardware targets such as multicore systems, [[Supercomputer|high performance computers]] and [[GPUs]]. It creates a new source code and thus allows the original source code of the application to remain unchanged.

===Cetus===

[[Cetus Source-to-source Translation Framework|Cetus]] is a compiler infrastructure for the source-to-source transformation of software programs. This project is developed by [[Purdue University]]. Cetus is written in [[Java (programming language)|Java]]. It provides basic infrastructure for writing automatic parallelization tools or compilers. The basic parallelizing techniques Cetus currently implements are [[privatization]], reduction variables recognition and [[induction variable]] substitution.

A new [[GUI|graphic user interface (GUI)]] was added in Feb 2013. [[Speedup]] calculations and graph display were added in May 2013. A Cetus remote server in a [[client–server model]] was added in May 2013 and users can optionally transform C Code through the server. This is especially useful when users run Cetus on a non-Linux platform. An experimental [[Nanohub|Hubzero]] version of Cetus was also implemented in May 2013 and users can also run Cetus through a web browser.

===PLUTO===

PLUTO is an automatic parallelization tool based on the [[polyhedral model]]. The polyhedral model for compiler optimization is a representation for programs that makes it convenient to perform high-level transformations such as [[loop nest optimization]]s and loop parallelization. Pluto transforms C programs from source to source for coarse-grained parallelism and data locality simultaneously. The core transformation framework mainly works by finding affine transformations for efficient tiling and fusion, but not limited to those. [[OpenMP]] parallel code for multicores can be automatically generated from sequential C program sections.

===Polaris compiler===

The Polaris compiler takes a Fortran77 program as input, transforms this program so that it runs efficiently on a [[parallel computer]], and outputs this program version in one of several possible parallel [[FORTRAN]] dialects. Polaris performs its transformations in several "compilation passes". In addition to many commonly known passes, Polaris includes advanced capabilities performing the following tasks: Array privatization, [[Data dependence]] testing, [[Induction variable]] recognition, Inter procedural analysis, and symbolic program analysis.

===Intel C++ compiler===

The auto-parallelization feature of the [[Intel C++ Compiler]] automatically translates serial portions of the input program into semantically equivalent [[multi-threaded]] code. Automatic parallelization determines the loops that are good work sharing candidates,
performs the data-flow analysis to verify correct parallel execution, and partitions the data for threaded code generation as is needed in
programming with [[OpenMP]] directives. The [[OpenMP]] and Auto-parallelization applications provide the performance gains from shared
memory on multiprocessor systems.

===Intel Advisor===
The [https://software.intel.com/en-us/intel-advisor-xe Intel Advisor 2017] is a vectorization optimization and thread prototyping tool. It integrates several steps into its workflow to search for parallel sites, enable users to mark loops for vectorization and threading, check loop-carried dependencies and memory access patterns for marked loops, and insert pragmas for vectorization and threading.

===AutoPar===

[[File:ROSE-autoPar-workflow.PNG|thumb|Workflow of the AutoPar tool]]
[https://en.wikibooks.org/wiki/ROSE_Compiler_Framework/autoPar AutoPar] is a tool which can automatically insert OpenMP pragmas into input serial C/C++ codes.  For input programs with existing OpenMP directives, the tool will double check the correctness when the right option is turned on. Compared to conventional tools, AutoPar can incorporate user knowledge (semantics) to discover more parallelization opportunities.

===iPat/OMP===

This tool provides users with the assistance needed for OpenMP parallelization of a sequential program. This tool is implemented as a set of functions on the Emacs editor. All the activities related to program parallelization, such as selecting a target portion of the program, invoking an assistance command, and modifying the program based on the assistance information shown by the tool, can be handled in the source program editor environment.<ref>“Development and Implementation of an Interactive Parallelization Assistance Tool for OpenMP: iPat/OMP” by Makoto Ishihara,Hiroki Honda and Mitsuhisa Sato</ref>

===Vienna Fortran compiler (VFC)===

It is a new source-to-source parallelization system for HPF+ (optimized version of HPF), which addresses the requirements of irregular
applications.

=== SUIF compiler ===

SUIF ([[Stanford University]] Intermediate Format) is a free infrastructure designed to support collaborative research in optimizing and parallelizing compilers. SUIF is a fully functional compiler that takes both Fortran and C as input languages. The parallelized code is output as an [[SPMD]] (Single Program Multiple Data) parallel C version of the program that can be compiled by native C compilers on a variety of architectures.<ref>"An Overview of the SUIF Compiler for Scalable Parallel Machines", In Proceedings of the Seventh SIAM Conference on Parallel Processing for Scientific Computing, 1993 by Saman P. Amarasinghe,Jennifer M. Anderson,Monica S. Lam,Chauwen Tseng</ref>

===Omni OpenMP compiler===

It translates [[C (programming language)|C]] and [[Fortran]] programs with [[OpenMP]] pragmas into C code suitable for compiling with a native compiler linked with the Omni OpenMP runtime library. It does for loop parallelization.

===Timing-Architects Optimizer===

It uses a simulation based approach to improve task allocation and task parallelization to multiple cores. By use of a simulation based performance and real-time analysis, different task allocation alternatives are benchmarked against each other. Dependencies as well as processor platform specific effects are considered. [https://web.archive.org/web/20141219215942/http://www.timing-architects.com/ta-tool-suite/optimizer.html TA Optimizer] is used in embedded system engineering.

===TRACO===

It uses the Iteration Space Slicing and Free Schedule Framework. The core is based on the Presburger Arithmetic and the transitive closure operation. Loop dependencies are represented with relations. TRACO uses the Omega Calculator, CLOOG and ISL libraries, and the Petit dependence analyser. The compiler extracts better locality with fine- and coarse-grained parallelism for C/C++ applications. The tool is developed by the West-Pomeranian University of Technology team; (Bielecki, Palkowski, Klimek and other authors) http://traco.sourceforge.net.

===SequenceL===

[[SequenceL]] is a general-purpose functional programming language and auto-parallelizing tool set, whose primary design objectives are performance on multi-core processor hardware, ease of programming, platform portability/optimization, and code clarity and readability. Its main advantage is that it can be used to write straightforward code that automatically takes full advantage of all the processing power available, without programmers needing to be concerned with identifying parallelisms, specifying vectorization, avoiding race conditions, and other challenges of manual directive-based programming approaches such as OpenMP.

Programs written in SequenceL can be compiled to multithreaded code that runs in parallel, with no explicit indications from a programmer of how or what to parallelize. As of 2015, versions of the SequenceL compiler generate parallel code in C++ and OpenCL, which allows it to work with most popular programming languages, including C, C++, C#, Fortran, Java, and Python. A platform-specific runtime manages the threads safely, automatically providing parallel performance according to the number of cores available.

===OMP2MPI===

OMP2MPI<ref>Albert Saa-Garriga, David Castells-Rufas, and Jordi Carrabina. 2015. OMP2MPI: Automatic MPI code generation from [[OpenMP]] programs. In High Performance Energy Efficient Embedded Systems. ACM.</ref> Automatically generates [[Message Passing Interface|MPI]] source code from [[OpenMP]]. Allowing that the program exploits non shared-memory architectures such as cluster, or Network-on-Chip based(NoC-based) multiprocessors-system-on-chip (MPSoC). OMP2MPI gives a solution that allow further optimization by an expert that want to achieve better results.

===OMP2HMPP===

OMP2HMPP,<ref>Albert Saa-Garriga, David Castells-Rufas, and Jordi Carrabina. 2014. OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions. In High Performance Energy Efficient Embedded Systems. ACM.</ref> a tool that, automatically translates a high-level C source code([[OpenMP]]) code into [[HMPP]]. The generated version rarely will differs from a hand-coded [[HMPP]] version, and will provide an important speedup, near 113%, that could be later improved by hand-coded [[CUDA]].

===emmtrix Parallel Studio===

[http://www.emmtrix.com/tools/emmtrix-parallel-studio emmtrix Parallel Studio] is a source-to-source parallelization tool combined with an interactive GUI developed by emmtrix Technologies GmbH. It takes C, [[MATLAB]], [[Simulink]], [[Scilab]] or [[Xcos]] source code as input and generates parallel C code as output. It relies on static schedule and a message passing API for the parallel program. The whole parallelization process is controlled and visualized in an interactive GUI enabling parallelization decisions by the end user. It targets embedded multicore architectures combined with GPU and FPGA accelerators.

===CLAW Compiler===

The [https://github.com/claw-project/claw-compiler CLAW Compiler] translates [[Fortran]] programs with claw pragmas into Fortran code suitable for a specific supercomputer target augmented with OpenMP or OpenACC pragmas.

===PaSH===
PaSH is parallelizing compiler for [[Unix shell]] scripts.<ref>((Cite web |last=Zewe |first=Adam |last2=Technology |first2=Massachusetts Institute of |title=Technique significantly boosts the speeds of programs that run in the Unix shell |url=https://techxplore.com/news/2022-06-technique-significantly-boosts-unix-shell.html |access-date=2022-06-08 |website=techxplore.com |language=en))</ref>
==See also==

*[[Automatic parallelization]]
*[[Intel C++ Compiler]]
*[[Scalable parallelism]]
*[[SequenceL]]
*[[BMDFM]]

==References==
((reflist))

==External links==
* [https://en.wikibooks.org/wiki/ROSE_Compiler_Framework/autoPar AutoPar]
* [http://pluto-compiler.sourceforge.net Pluto-compiler]
* [http://www.par4all.org/features par4all]
* [http://cetus.ecn.purdue.edu Cetus]
* [http://traco.sourceforge.net Traco]
* [https://github.com/sdruix/OMP2MPI OMP2MPI]
* [https://github.com/sdruix/OMP2HMPP OMP2HMPP]
* [http://www.emmtrix.com/tools/emmtrix-parallel-studio emmtrix Parallel Studio]

[[Category:Parallel computing]]

Pages transcluded onto the current version of this page (help):

Automatic parallelization tool (edit)
Template:Ambox (view source) (template editor protected)
Template:Ambox globe (view source) (template editor protected)
Template:Ambox globe current red (view source) (template editor protected)
Template:Cite web (view source) (protected)
Template:Find sources mainspace (view source) (template editor protected)
Template:Main other (view source) (protected)
Template:More citations needed (view source) (template editor protected)
Template:Outdated (view source) (semi-protected)
Template:Pagetype (view source) (protected)
Template:Refimprove (view source) (template editor protected)
Template:Reflist (view source) (protected)
Template:Reflist/styles.css (view source) (protected)
Template:SDcat (view source) (protected)
Template:SUBJECTSPACE formatted (view source) (template editor protected)
Template:Short description (view source) (protected)
Template:Short description/lowercasecheck (view source) (protected)
Template:Update (view source) (template editor protected)
Module:Arguments (view source) (protected)
Module:Category handler (view source) (protected)
Module:Category handler/blacklist (view source) (protected)
Module:Category handler/config (view source) (protected)
Module:Category handler/data (view source) (protected)
Module:Category handler/shared (view source) (protected)
Module:Check for unknown parameters (view source) (protected)
Module:Citation/CS1 (view source) (protected)
Module:Citation/CS1/COinS (view source) (protected)
Module:Citation/CS1/Configuration (view source) (protected)
Module:Citation/CS1/Date validation (view source) (protected)
Module:Citation/CS1/Identifiers (view source) (protected)
Module:Citation/CS1/Utilities (view source) (protected)
Module:Citation/CS1/Whitelist (view source) (protected)
Module:Citation/CS1/styles.css (view source) (protected)
Module:Disambiguation/templates (view source) (protected)
Module:Find sources (view source) (template editor protected)
Module:Find sources/config (view source) (template editor protected)
Module:Find sources/links (view source) (template editor protected)
Module:Find sources/templates/Find sources mainspace (view source) (template editor protected)
Module:Message box (view source) (protected)
Module:Message box/ambox.css (view source) (protected)
Module:Message box/configuration (view source) (protected)
Module:Namespace detect/config (view source) (protected)
Module:Namespace detect/data (view source) (protected)
Module:Pagetype (view source) (protected)
Module:Pagetype/config (view source) (protected)
Module:Pagetype/disambiguation (view source) (protected)
Module:Pagetype/setindex (view source) (protected)
Module:Pagetype/softredirect (view source) (protected)
Module:SDcat (view source) (protected)
Module:String (view source) (protected)
Module:Unsubst (view source) (protected)
Module:Wikitext Parsing (view source) (protected)
Module:Yesno (view source) (protected)

Return to Automatic parallelization tool.

Retrieved from "https://en.wikipedia.org/wiki/Automatic_parallelization_tool"