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[ [http://ctuning.org/wiki/index.php/Special:CPredict Predict optimizations (on-going)] ]<BR><BR>
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Revision as of 09:50, 26 April 2009

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Collective Optimization Database

Sharing and reusing optimization knowledge
News
  • 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.29 - Intel just made an announcement about "An Intelligent Approach to IT Challenges" which shares some of our vision except that there is still no collective optimization and machine learning. However, it's really a good motivation for our project!..
  • 2009.January.20 - We went off-line to move to a new hosting and a new Mediawiki platform.

  • 2008.October.17 - First public version of cDatabase is ready.

  • 2007.March.03 - cDatabase has been extended for the MILEPOST project.

Collective Optimization Database (cDatabase or COD) provides a common global repository with data analysis plugins to share, reuse and reference interesting program/architecture optimization cases. It has been developed to help users optimize programs, libraries, kernels and the whole systems (compiler optimizations/architecture configurations to improve execution time, code size, architecture size, power consumption, etc). It is intended to simplify and automate the design and optimization of programs, compilers, run-time systems and architectures based on recent statistical and machine learning techniques (FT2009, FMTP2008, ABCP2006, MILEPOST, UNIDAPT). We also hope that it will also be useful for adaptive parallelization and scheduling for the emerging and future heterogeneous multi-core systems including current CPU/GPU and CELL architectures (LCWP2009). Finally, it is intended to improve the quality of academic research by avoiding costly duplicate experiments and providing replicable referable results. It can provide detailed performance analysis and comparison of different programs, datasets, compilers and architectures. It can be used to optimize programs on-the-fly when using cloud computing services.

We currently keep information about architectures and their configurations, software environments, programs, datasets, compilers (such as GCC, Open64, ICC, PathScale and plan to add dynamic compilers such as LLVM, IBM Testerossa, etc), compiler flags for program and architecture optimizations, compiler ICI optimization passes, fine-grain program optimizations, execution time, code size, profiling statistics, program static and dynamic features (hardware counters), parallelization schemes, etc.

cDatabase is an evolving project driven by the community and industry demands - you are welcome to join the project, extend the database and data analysis plugins, provide feedback and add your optimization data to help the community. If you want to use database directly, you can find more info about cDatabase API and web-services in cDatabase documentation. You can also communicate with cTuning community through our mailing lists.


cDatabase friends:
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You are welcome to register your interest at this page.
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