chunosov / crowdsource-video-experiments-on-desktop

CK demo on crowdsourcing video experiments on desktop (Windows, Linux) using Qt

Introduction

This [CK-powered] (http://github.com/ctuning/ck) open-source cross-platform desktop demo app (at least, for Linux and Windows) based on QT to recognize images via Caffe or TensorFlow, and send reports (timing/correctness/etc) to CK.

You can download this app from the Google Play Store.

You can also find public results at Live CK repo!

Public scenarios are prepared using this CK GitHub repo. Caffe libraries are generated using CK-Caffe framework.

Current scenarios include multi-dimensional and multi-objective optimization of benchmarks and real workloads such as Caffe, TensorFlow and other DNN frameworks in terms of performance, accuracy, energy, memory footprint, cost, etc.

See our vision paper.

Related projects:

• hhttps://github.com/dividiti/crowdsource-video-experiments-on-android/issues

License

• Permissive 3-clause BSD license. (See LICENSE.txt for more details).

Minimal requirements

Linux, Windows or MacOS operation system

Authors

• Daniil Efremov
• Grigori Fursin (original crowd-tuner: https://github.com/ctuning/crowdsource-experiments-using-android-devices)
• Anton Lokhmotov

Privacy Policy

This application requires access to your Camera to let you capture images, recognize them and collect various performance statistics. Note that, by default, no images are sent to public servers! Only if misprediction happens, you are encouraged but not obliged (!) to submit incorrectly recognized image with the correct label to the public server to help the community enhance existing data sets with new images!

Questions/comments/discussions?

Please subscribe to our mailing lists:

• Open, collaborative and reproducible R&D including knowledge preservation, sharing and reuse: http://groups.google.com/group/collective-knowledge
• Software and hardware multi-objective (performance/energy/accuracy/size/reliability/cost) benchmarking, autotuning, crowdtuning and run-time adaptation: http://groups.google.com/group/ctuning-discussions

Publications

The concepts have been described in the following publications:

• http://arxiv.org/abs/1506.06256 (CPC'15)
• http://bit.ly/ck-date16 (DATE'16)
• http://hal.inria.fr/hal-01054763 (Journal of Scientific Programming'14)
• https://hal.inria.fr/inria-00436029 (GCC Summit'09)

If you found this app useful for your R&D, you are welcome to reference any of the above publications in your articles and reports. You can download all above references in one BibTex file here.

Testimonials and awards

• 2014: HiPEAC technology transfer award: HiPEAC TT winners
• 2015: ARM and the cTuning foundation use CK to accelerate computer engineering: HiPEAC Info'45 page 17, ARM TechCon'16 presentation and demo, public CK repo

Acknowledgments

CK development is coordinated by dividiti and the cTuning foundation (non-profit research organization) We are also extremely grateful to all volunteers for their valuable feedback and contributions.