From cTuning.org
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*'''2009.September.1''' - The documentation of [http://ctuning.org/milepost-gcc MILEPOST GCC]/[http://ctuning.org/ici GCC ICI] extensions by Yuanjie and Liang during GSOC'09 program is now available: [http://ctuning.org/wiki/index.php/CTools:ICI:Projects:GSOC09:Function_cloning_and_program_instrumentation Function cloning and program instrumentation] and [http://ctuning.org/wiki/index.php/CTools:ICI:Projects:GSOC09:Fine_grain_tuning Fine grain program tuning]. We would like to fully test and sync these developments with mainline GCC within next month or two. | *'''2009.September.1''' - The documentation of [http://ctuning.org/milepost-gcc MILEPOST GCC]/[http://ctuning.org/ici GCC ICI] extensions by Yuanjie and Liang during GSOC'09 program is now available: [http://ctuning.org/wiki/index.php/CTools:ICI:Projects:GSOC09:Function_cloning_and_program_instrumentation Function cloning and program instrumentation] and [http://ctuning.org/wiki/index.php/CTools:ICI:Projects:GSOC09:Fine_grain_tuning Fine grain program tuning]. We would like to fully test and sync these developments with mainline GCC within next month or two. | ||
- | *'''2009.August.05''' - The colleagues from the [http://unidapt.org UNIDAPT Group] started investigating the use of [http://ctuning.org cTuning]/[http://cTuning.org/project-milepost MILEPOST] technology and the [http://ctuning.org/unidapt UNIDAPT framework] to predict good optimization and parallelization schemes for hybrid heterogeneous CPU/GPU-like architectures together with [http://www.caps-entreprise.com CAPS Entreprise] based on run-time adaptation and profiling, empirical iterative compilation, statistical analysis, machine learning, program and dataset features and run-time decision trees ({{Ref|FT2009}}, {{Ref|LCWP2009}}, {{Ref|Fur2009}}, {{Ref|JGVP2009}}, {{Ref1|TWFP2009}}, {{Ref|FMTP2008}}, {{Ref|LFF2007}}, {{Ref|FCOP2005}}). They plan to add new optimization cases to the [http://ctuning.org/cdatabase Collective Optimization Database] in Autumn, 2009. | + | *'''2009.August.05''' - The colleagues from the [http://unidapt.org UNIDAPT Group] started investigating the use of [http://ctuning.org cTuning]/[http://cTuning.org/project-milepost MILEPOST] technology and the [http://ctuning.org/unidapt UNIDAPT framework] to predict good optimization and parallelization schemes for hybrid heterogeneous CPU/GPU-like architectures together with [http://www.caps-entreprise.com CAPS Entreprise] based on run-time adaptation and profiling, empirical iterative compilation, statistical analysis, machine learning, program and dataset features and run-time decision trees ({{Ref|FT2010}}, {{Ref|FT2009}}, {{Ref|LCWP2009}}, {{Ref|Fur2009}}, {{Ref|JGVP2009}}, {{Ref1|TWFP2009}}, {{Ref|FMTP2008}}, {{Ref|LFF2007}}, {{Ref|FCOP2005}}). They plan to add new optimization cases to the [http://ctuning.org/cdatabase Collective Optimization Database] in Autumn, 2009. |
*'''2009.July.27''' - The paper "Portable Compiler Optimization Across Embedded Programs and Microarchitectures using Machine Learning" ({{Ref|DJBP2009}}) has been accepted for the [http://www.microarch.org/micro42 42nd IEEE/ACM International Symposium on Microarchitecture (MICRO)]. The research has been led by the colleagues from the University of Edinburgh - congratulations! | *'''2009.July.27''' - The paper "Portable Compiler Optimization Across Embedded Programs and Microarchitectures using Machine Learning" ({{Ref|DJBP2009}}) has been accepted for the [http://www.microarch.org/micro42 42nd IEEE/ACM International Symposium on Microarchitecture (MICRO)]. The research has been led by the colleagues from the University of Edinburgh - congratulations! | ||
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*'''2009.June.26''' - The pdf of the paper that describes Collective Tuning Infrastructure and cTuning concept (presented at the GCC Summit'09) will be available in a few weeks [http://unidapt.org/index.php/Dissemination#Fur2009 here]. | *'''2009.June.26''' - The pdf of the paper that describes Collective Tuning Infrastructure and cTuning concept (presented at the GCC Summit'09) will be available in a few weeks [http://unidapt.org/index.php/Dissemination#Fur2009 here]. | ||
- | *'''2009.June.10''' - Extended version of the "Collective Optimization" paper ({{Ref|FT2009|}}) describing collective tuning concept has been accepted for ACM Transactions on Architecture and Code Optimization (TACO). | + | *'''2009.June.10''' - Extended version of the "Collective Optimization" paper ({{Ref|FT2010}},{{Ref|FT2009|}}) describing collective tuning concept has been accepted for ACM Transactions on Architecture and Code Optimization (TACO). |
* '''2009.June.01''' - After nearly 1 year of developments we released/updated all our open-source collaborative [[CTools|R&D tools]]: | * '''2009.June.01''' - After nearly 1 year of developments we released/updated all our open-source collaborative [[CTools|R&D tools]]: |
Revision as of 00:06, 31 December 2010
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Collective Benchmark |
Enabling realistic benchmarking and optimization |
Web shortcut: http://cTuning.org/cbench Navigation: cTuning.org > CTools Collective Benchmark (cBench) is a collection of open-source sequential programs (working to add parallel applications) with multiple datasets (former MiDataSets) assembled by the community to enable realistic benchmarking and research on program and architecture optimization. The source code of individual programs is simplified to ease portability. All the benchmarks now include scripts to be used with Continuous Collective Compilation Framework to perform automatic optimizations (iterative compilation) using GCC, LLVM, GCC4CIL, Open64, PathScale, Intel and other compilers and a wide range of architectures. This collection of programs can later be used to create specialized benchmarks. cBench is an evolving project driven by the community demands - you are welcome to join the project, extend or add benchmarks and datasets and provide performance analysis, leave feedback and add your optimization data to the Collective Optimization Database to help the community optimize their programs. You can also communicate with cTuning community through our mailing lists.
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cBench is an open collaborative community-driven project. You are welcome to join us and participate in discussions, developments or provide feedback and suggestions to extend cBench or add new benchmarks/datasets.