Conclusion

[ROUGH] Jupyter in HPC is now commonplace. We have been able to give hundreds of HPC users a rich user interface to HPC through Jupyter. In the supercomputing context, we look at Jupyter as a tool that will help make it easier for our users to take advantage of supercomputing hardware and software. Some of that will come from us at supercomputing centers. Jupyter as a project needs to not make design decisions that break things for us, or lock us into one way of doing things. Each HPC center is different and that means that for Jupyter to remain useful to HPC centers and supercomputing it needs to maintain its high level of abstraction. We should make this into a bulleted list of demands :)

Acknowledgments

This work was supported by Lawrence Berkeley National Laboratory, through the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory.