We describe Joshua, an open source toolkit for statistical machine translation. 

Joshua implements all of the algorithms required for translation via synchronous context free grammars (SCFGs): 
chart-parsing, n-gram language model integration, beam- and cube-pruning, and k-best extraction. 

The toolkit also implements suffix-array grammar extraction and minimum error rate training. 

It uses parallel and distributed computing techniques for scalability. 

We also provide a demonstration outline for illustrating the toolkit's features to potential users, whether they be newcomers to the field or power users interested in extending the toolkit.