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* '''2009.April.21''' - [http://socghop.appspot.com/org/home/google/gsoc2009/gcc Several projects] to enable automatic fine-grain program optimization and run-time adaptation in GCC using iterative compilation and machine learning (based on our cTuning/UNIDAPT/ICI/MILEPOST technology) have been accepted by the Google Summer of Code. You are welcome to [[Join|join cTuning community]] and follow or participate in the developments using our dedicated [[Community|mailing lists]].
* '''2009.April.21''' - [http://socghop.appspot.com/org/home/google/gsoc2009/gcc Several projects] to enable automatic fine-grain program optimization and run-time adaptation in GCC using iterative compilation and machine learning (based on our cTuning/UNIDAPT/ICI/MILEPOST technology) have been accepted by the Google Summer of Code. You are welcome to [[Join|join cTuning community]] and follow or participate in the developments using our dedicated [[Community|mailing lists]].
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* '''2009.April.15''' - Rice University made an announcement about [http://www.eurekalert.org/pub_releases/2009-04/ru-rpa040709.php a DARPA grant to improve compilers for heterogeneous architectures] - this is yet another good motivation for our work since many similar techniques and open-source tools are already being developed by the cTuning community ([[CTools|cTools]]), within the [http://www.milepost.eu MILEPOST project] and [http://www.hipeac.net HiPEAC network] thus showing the power of collaborative R&D ;) ...
 
* '''2009.March.08''' - CCC pre-release version has been uploaded to the SVN. We are currently documenting it.
* '''2009.March.08''' - CCC pre-release version has been uploaded to the SVN. We are currently documenting it.

Revision as of 17:02, 11 May 2009

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Continuous Collective Compilation Framework

Enabling collective optimization
News
  • 2009.April.27 - We gave a talk at the University of Illinois at Urbana-Champaign about Collective Tuning Initiative and tools and MILEPOST project ("Collective Optimization, run-time adaptation and machine learning"). Presentation is available here. We would like to thank all the UIUC colleagues for a very interesting and useful feedback.
  • 2009.April.21 - Several projects to enable automatic fine-grain program optimization and run-time adaptation in GCC using iterative compilation and machine learning (based on our cTuning/UNIDAPT/ICI/MILEPOST technology) have been accepted by the Google Summer of Code. You are welcome to join cTuning community and follow or participate in the developments using our dedicated mailing lists.
  • 2009.March.08 - CCC pre-release version has been uploaded to the SVN. We are currently documenting it.
Navigation: cTuning.org > CTools 

Continuous Collective Compilation Framework (CCC) is a collaborative modular plugin-enabled R&D infrastructure to automate program and architecture optimizations (i.e. iteratively search for good program and architecture optimizations in a feedback-directed manner) and gather various static and dynamic optimization profile data in a Collective Optimization Database. It supports both global program optimization and fine-grain procedure, loop or instruction level optimizations if compiler supports Interactive Compilation Interface. It is used to help end-users optimize their programs, libraries and whole OS automatically (improve execution time/code size, etc), test and tune compiler optimization heuristic. It also enables collaborative R&D and optimization knowledge reuse with statistical and machine learning techniques (FMTP2008, FT2009).

CCC Framework is a community-driven project - you are welcome to join the project, extend it, provide smart search and data analysis plugins, leave feedback and add your optimization data to help the community. You can also communicate with cTuning community through our mailing lists.


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You are welcome to join us and participate in CCC developments, discussions, provide feedback or suggestions to extend CCC or add new functionality. The framework currently supports multiple compilers including GCC, Open64, PathScale, Intel ICC, IBM XLC and a large number of server, desktop and embedded architectures.

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