You need to launch the notebook in parallel using an MPI parallel IPython cluster. In addition, you will need to configure the notebook to hook into IPython's built-in parallelism.
I've uploaded a notebook that uses parallel IPython here:
Note that all the yt operations aren't really important, but the first few cells where I check to make sure IPython's parallelism works and that MPI parllelism is working are quite important.
Note also that you will need to launch the IPython cluster separately from the notebook server using the "ipcluster" command.
All that said, it does add a significant amount of semantic overhead to use the IPython notebook in parallel. It's generally much more straightforward to work with yt in parallel using regular python scripts.
Hope that helps,