CK-Caffe
Collective Knowledge repository for optimising Caffe-based designs
CK-Caffe is an open framework for collaborative and reproducible optimisation of convolutional neural networks. It's based on the Caffe framework from the Berkeley Vision and Learning Center (BVLC) and the Collective Knowledge framework from the cTuning Foundation. In essence, CK-Caffe is simply a suite of convenient wrappers for building, evaluating and optimising performance of Caffe.
As outlined in our vision, we invite the community to collaboratively design and optimize convolutional neural networks to meet the performance, accuracy and cost requirements for deployment on a range of form factors - from sensors to self-driving cars. To this end, CK-Caffe leverages the key capabilities of CK to crowdsource experimentation across diverse platforms, CNN designs, optimization options, and so on; exchange experimental data in a flexible JSON-based format; and apply leading-edge predictive analytics to extract valuable insights from the experimental data.
https://github.com/dividiti/ck-caffe/blob/master/README.md
#deeplearning #caffe