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https://github.com/ctuning/ck-autotuning

CK automation actions to let users implement portable, customizable and reusable program workflows for reproducible, collaborative and multi-objective benchmarking, optimization and SW/HW co-design:
https://github.com/ctuning/ck-autotuning

actions android autotuning codereef collective-knowledge json-api linux macos multiple-dimensions multiple-objectives pareto portable-workflows program python statistical-analysis windows workflow

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CK automation actions to let users implement portable, customizable and reusable program workflows for reproducible, collaborative and multi-objective benchmarking, optimization and SW/HW co-design:

Awesome Lists containing this project

README 

        
Universal, customizable and multi-objective software and hardware autotuning

============================================================================



**All CK components can be found at [cKnowledge.io](https://cKnowledge.io) and in [one GitHub repository](https://github.com/ctuning/ck-mlops)!**



*This project is hosted by the [cTuning foundation](https://cTuning.org).*



[![compatibility](https://github.com/ctuning/ck-guide-images/blob/master/ck-compatible.svg)](https://github.com/ctuning/ck)

[![automation](https://github.com/ctuning/ck-guide-images/blob/master/ck-artifact-automated-and-reusable.svg)](http://cTuning.org/ae)

[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)



Linux & MacOS: [![Travis Build Status](https://travis-ci.org/ctuning/ck-autotuning.svg?branch=master)](https://travis-ci.org/ctuning/ck-autotuning)

Windows: [![AppVeyor Build status](https://ci.appveyor.com/api/projects/status/github/ctuning/ck-autotuning?branch=master&svg=true)](https://ci.appveyor.com/project/ens-lg4/ck-autotuning)



This is a [CK repository](https://github.com/ctuning/ck) for the universal, customizable, 

multi-dimensional and multi-objective SW/HW benchmarking, autotuning 

and co-design with a unified JSON API across Linux, Android, MacOS 

and Windows-based machines.



![logo](https://github.com/ctuning/ck-guide-images/blob/master/image-pipelines2.png)



This repository included CK modules, actions and components for unified



* program compilation and execution (with multiple data sets)

* crowd-benchmarking

* statistical analysis of empirical results

* plugin-based autotuning

* automatic performance modeling

* static and dynamic features extraction

* learning to predict optimizations and run-time adaptation

* reproducibility of experimental results



Further info:

* [Shared portable CK program workflows](https://cKnowledge.io/programs)

* [Open CK platform to publish and download stable CK components](https://cKnowledge.io/docs)

* [MLPerf crowd-benchmarking demo](https://cknowledge.io/demo)

* [Documentation about portable CK workflows](https://github.com/ctuning/ck/wiki/Portable-workflows)

* [Related CK publications](https://github.com/ctuning/ck/wiki/Publications)



Author

======

* [Grigori Fursin](https://fursin.net)



Contributors

============

* See the list of [contributors](https://github.com/ctuning/ck-autotuning/blob/master/CONTRIBUTIONS)



Shared CK modules with actions

==============================



* [program](https://cKnowledge.io/c/module/program)

* [program.output](https://cKnowledge.io/c/module/program.output)

* [pipeline](https://cKnowledge.io/c/module/pipeline)

* [pipeline.cmd](https://cKnowledge.io/c/module/pipeline.cmd)

* [platform.gpgpu](https://cKnowledge.io/c/module/platform.gpgpu)

* [algorithm](https://cKnowledge.io/c/module/algorithm)

* [choice](https://cKnowledge.io/c/module/choice)

* [compiler](https://cKnowledge.io/c/module/compiler)

* [dataset](https://cKnowledge.io/c/module/dataset)

* [dataset.features](https://cKnowledge.io/c/module/dataset.features)

* [program.behavior](https://cKnowledge.io/c/module/program.behavior)

* [program.dynamic.features](https://cKnowledge.io/c/module/program.dynamic.features)

* [program.experiment.speedup](https://cKnowledge.io/c/module/program.experiment.speedup)

* [program.species](https://cKnowledge.io/c/module/program.species)

* [program.static.features](https://cKnowledge.io/c/module/program.static.features)



Installation

============



First install the CK framework as described [here](https://github.com/ctuning/ck#installation).



Then install this CK repository as follows:



```

 $ ck pull repo:ck-autotuning



```



You can now browse and reuse program workflows shared at the [CK portal](https://cKnowledge.io/programs).



Please refer to the [CK online guides](https://github.com/ctuning/ck/wiki)

including [CK portable workflows](https://github.com/ctuning/ck/wiki/Portable-workflows)

and the [autotuning example](https://github.com/ctuning/ck/wiki/Autotuning).



Troubleshooting

===============

* Issues with GLIBCXX_3.4.20/3.4.21 when using LLVM installed via CK: These sometimes occur on earlier Ubuntu versions (14.04) 

  on ARM/x86. This can be fixed by upgrading to later versions of Ubuntu, or can sometimes be fixed by:



```

 $ sudo add-apt-repository ppa:ubuntu-toolchain-r/test

 $ sudo apt-get update

 $ sudo apt-get upgrade

 $ sudo apt-get dist-upgrade

```



* Issues with libncursesw.so.6 (not found) on some older machines: It can be fixed 

  by compiling and installing lib-ncurses with the support for wide characters. This can be done automatically via CK:



```

 $ ck install package:lib-ncurses-6.0-root

```



Questions and comments

======================



Please feel free to get in touch with the [CK community](https://github.com/ctuning/ck/wiki/Contacts) 

if you have any questions, suggestions and comments!