From cTuning.org
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| - | *'''2009.August.05''' - The colleagues from the [http://unidapt.org UNIDAPT Group] started investigating the use of [http://ctuning.org cTuning]/[http://www.milepost.eu MILEPOST] technology and the [http://ctuning.org/unidapt UNIDAPT framework] to predict good optimization and parallelization schemes for hybrid heterogeneous CPU/GPU-like architectures based on statistical analysis, machine learning, program and dataset features and run-time decision trees | + | *'''2009.August.05''' - The colleagues from the [http://unidapt.org UNIDAPT Group] started investigating the use of [http://ctuning.org cTuning]/[http://www.milepost.eu 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.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! | ||
Revision as of 11:09, 7 August 2009
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Collective Benchmark |
| Enabling realistic benchmarking and optimization |
Navigation: cTuning.org > CTools Collective Benchmark (cBench) is a collection of open-source sequential and parallel programs with multiple datasets 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.