"We''ll demonstrate how Python and the Numba JIT compiler can be used for
GPU programming that easily scales from your workstation to an Apache
Spark cluster. Using an example application, we show how to write CUDA
kernels in Python, compile and call them using the open source Numba JIT
compiler, and execute them both locally and remotely with Spark. We
also describe techniques for managing Python dependencies in a Spark
cluster with the tools in the Anaconda Platform. Finally, we conclude
with some tips and tricks for getting best performance when doing GPU
computing with Spark and Python."
http://on-demand.gputechconf.com/gtc/2016/presentation/s6413-stanley-seibert-apache-spark-python.pdf
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