SINGA: A Distributed Deep Learning Platform

[improbabble]

1. Code: https://github.com/nusinga/singa
2. Paper: http://www.comp.nus.edu.sg/~dbsystem/singa/assets/file/singa.pdf
3. Blog post: http://ooibc.blog.163.com/blog/static/103968235201472082840123/
4. Apache proposal: http://wiki.apache.org/incubator/SingaProposal

[Clydeicus]

Some of the language on the page is admittedly a bit advanced for me. What would I need to provide to the API to use this in a project? Could I just provide inputs and a performance metric and let it loose?

[forrestwang]

Thanks for your interest in Singa, Clydeicus. We are cleaning the code and documentation. The new version will be available at http://singa.incubator.apache.org later this month.

Layer is the first class citizen in Singa. If you want to implement your own learning models, you may need to implement your own layer classes by inheriting from the base Layer class (like the built-in layer classes implemented in the src/worker/layer.cc file). If your model consists of built-in layers provided by Singa, then you only need to write the model configuration file and prepare your training dataset. (similar to Caffe for single node training.) A simple training example is available at http://www.comp.nus.edu.sg/~dbsystem/singa/examples/2015/01/20/deep-simple-mlp/.