{"id":13936754,"url":"https://github.com/ctuning/ck-autotuning","last_synced_at":"2026-01-22T19:22:38.238Z","repository":{"id":25573478,"uuid":"29007219","full_name":"ctuning/ck-autotuning","owner":"ctuning","description":"CK automation actions to let users implement portable, customizable and reusable program workflows for reproducible, collaborative and multi-objective benchmarking, optimization and SW/HW 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customizable and multi-objective software and hardware autotuning\n============================================================================\n\n**All CK components can be found at [cKnowledge.io](https://cKnowledge.io) and in [one GitHub repository](https://github.com/ctuning/ck-mlops)!**\n\n*This project is hosted by the [cTuning foundation](https://cTuning.org).*\n\n[![compatibility](https://github.com/ctuning/ck-guide-images/blob/master/ck-compatible.svg)](https://github.com/ctuning/ck)\n[![automation](https://github.com/ctuning/ck-guide-images/blob/master/ck-artifact-automated-and-reusable.svg)](http://cTuning.org/ae)\n[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)\n\nLinux \u0026 MacOS: [![Travis Build Status](https://travis-ci.org/ctuning/ck-autotuning.svg?branch=master)](https://travis-ci.org/ctuning/ck-autotuning)\nWindows: [![AppVeyor Build status](https://ci.appveyor.com/api/projects/status/github/ctuning/ck-autotuning?branch=master\u0026svg=true)](https://ci.appveyor.com/project/ens-lg4/ck-autotuning)\n\nThis is a [CK repository](https://github.com/ctuning/ck) for the universal, customizable, \nmulti-dimensional and multi-objective SW/HW benchmarking, autotuning \nand co-design with a unified JSON API across Linux, Android, MacOS \nand Windows-based machines.\n\n![logo](https://github.com/ctuning/ck-guide-images/blob/master/image-pipelines2.png)\n\nThis repository included CK modules, actions and components for unified\n\n* program compilation and execution (with multiple data sets)\n* crowd-benchmarking\n* statistical analysis of empirical results\n* plugin-based autotuning\n* automatic performance modeling\n* static and dynamic features extraction\n* learning to predict optimizations and run-time adaptation\n* reproducibility of experimental results\n\nFurther info:\n* [Shared portable CK program workflows](https://cKnowledge.io/programs)\n* [Open CK platform to publish and download stable CK components](https://cKnowledge.io/docs)\n* [MLPerf crowd-benchmarking demo](https://cknowledge.io/demo)\n* [Documentation about portable CK workflows](https://github.com/ctuning/ck/wiki/Portable-workflows)\n* [Related CK publications](https://github.com/ctuning/ck/wiki/Publications)\n\nAuthor\n======\n* [Grigori Fursin](https://fursin.net)\n\nContributors\n============\n* See the list of [contributors](https://github.com/ctuning/ck-autotuning/blob/master/CONTRIBUTIONS)\n\nShared CK modules with actions\n==============================\n\n* [program](https://cKnowledge.io/c/module/program)\n* [program.output](https://cKnowledge.io/c/module/program.output)\n* [pipeline](https://cKnowledge.io/c/module/pipeline)\n* [pipeline.cmd](https://cKnowledge.io/c/module/pipeline.cmd)\n* [platform.gpgpu](https://cKnowledge.io/c/module/platform.gpgpu)\n* [algorithm](https://cKnowledge.io/c/module/algorithm)\n* [choice](https://cKnowledge.io/c/module/choice)\n* [compiler](https://cKnowledge.io/c/module/compiler)\n* [dataset](https://cKnowledge.io/c/module/dataset)\n* [dataset.features](https://cKnowledge.io/c/module/dataset.features)\n* [program.behavior](https://cKnowledge.io/c/module/program.behavior)\n* [program.dynamic.features](https://cKnowledge.io/c/module/program.dynamic.features)\n* [program.experiment.speedup](https://cKnowledge.io/c/module/program.experiment.speedup)\n* [program.species](https://cKnowledge.io/c/module/program.species)\n* [program.static.features](https://cKnowledge.io/c/module/program.static.features)\n\nInstallation\n============\n\nFirst install the CK framework as described [here](https://github.com/ctuning/ck#installation).\n\nThen install this CK repository as follows:\n\n```\n $ ck pull repo:ck-autotuning\n\n```\n\nYou can now browse and reuse program workflows shared at the [CK portal](https://cKnowledge.io/programs).\n\nPlease refer to the [CK online guides](https://github.com/ctuning/ck/wiki)\nincluding [CK portable workflows](https://github.com/ctuning/ck/wiki/Portable-workflows)\nand the [autotuning example](https://github.com/ctuning/ck/wiki/Autotuning).\n\nTroubleshooting\n===============\n* Issues with GLIBCXX_3.4.20/3.4.21 when using LLVM installed via CK: These sometimes occur on earlier Ubuntu versions (14.04) \n  on ARM/x86. This can be fixed by upgrading to later versions of Ubuntu, or can sometimes be fixed by:\n\n```\n $ sudo add-apt-repository ppa:ubuntu-toolchain-r/test\n $ sudo apt-get update\n $ sudo apt-get upgrade\n $ sudo apt-get dist-upgrade\n```\n\n* Issues with libncursesw.so.6 (not found) on some older machines: It can be fixed \n  by compiling and installing lib-ncurses with the support for wide characters. This can be done automatically via CK:\n\n```\n $ ck install package:lib-ncurses-6.0-root\n```\n\nQuestions and comments\n======================\n\nPlease feel free to get in touch with the [CK community](https://github.com/ctuning/ck/wiki/Contacts) \nif you have any questions, suggestions and comments!\n","funding_links":[],"categories":["Python"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fctuning%2Fck-autotuning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fctuning%2Fck-autotuning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fctuning%2Fck-autotuning/lists"}