Ron Bekkerman initiated an effort to create an edited book on parallel machine learning that Misha and I have been helping with. The breadth of efforts to parallelize machine learning surprised me: I was only aware of a small fraction initially.
This put us in a unique position, with knowledge of a wide array of different efforts, so it is natural to put together a survey tutorial on the subject of parallel learning for KDD, tomorrow. This tutorial is not limited to the book itself however, as several interesting new algorithms have come out since we started inviting chapters.
This tutorial should interest anyone trying to use machine learning on significant quantities of data, anyone interested in developing algorithms for such, and of course who has bragging rights to the fastest learning algorithm on planet earth
(Also note the Modeling with Hadoop tutorial just before ours which deals with one way of trying to speed up learning algorithms. We have almost no overlap.)