From cTuning.org
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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 ({{Ref|FT2009}}, {{Ref|FMTP2008}}, {{Ref|ABCP2006}}, [http://www.milepost.eu MILEPOST], [http://unidapt.org UNIDAPT]). It is also intended to improve the quality of academic research by avoiding | 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 ({{Ref|FT2009}}, {{Ref|FMTP2008}}, {{Ref|ABCP2006}}, [http://www.milepost.eu MILEPOST], [http://unidapt.org UNIDAPT]). It is also 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. | + | 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 [[CTools:ICI|ICI]] optimization passes, fine-grain program optimizations, execution time, code size, profiling statistics, program static and dynamic features (hardware counters), parallelization schemes, etc. | 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 [[CTools:ICI|ICI]] optimization passes, fine-grain program optimizations, execution time, code size, profiling statistics, program static and dynamic features (hardware counters), parallelization schemes, etc. | ||
Revision as of 20:59, 25 March 2009
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Collective Optimization Database |
| Sharing and reusing optimization knowledge |
| News |
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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). It is also 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: |
       
You are welcome to register your interest at this page. |