CK workflow and reproducible article: "A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques"
- 1. cTuning foundation and dividiti
- 2. dividiti
- 3. Xored
- 4. Raspberry Pi Foundation
Description
This repository contains a snapshot of a Collective Knowledge workflow with a reproducible article for collaborative research into multi-objective autotuning and machine learning techniques. It supports our long-term community initiative to improve reproducibility of experimental results from published papers, automate artifact evaluation, and help the community share code, data and workflows as reusable components!
You can find more details about our approach in this reproducible and interactive article automatically generated by this CK workflow: http://cKnowledge.org/rpi-crowd-tuning . Shared results from crowd-tuning across diverse devices provided by volunteers are available in a reproducible form in this repository: http://cknowledge.org/repo-beta .
Files
ck-repository-rpi-optimization-results-20181220.zip
Files
(389.9 MB)
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md5:f80be8a36e5553940936655b6832213e
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md5:09220898e6926c7c80ec17221ddd798a
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Additional details
Related works
- Is supplement to
- https://arxiv.org/abs/1801.08024 (URL)
References
- Fursin, Grigori (2018). "A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques", arXiv:1801.08024