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- 7/18: received notice that Einstein Toolkit School and Workshop hosted at NCSA was looking for a solution to host a tutorial for the Einstein Toolkit using Jupyter notebooks. They were exploring Jupyterhub, but also open to considering Workbench
- 7/20: Met with organizer to discuss potential requirements and demonstrate what we've done for PI4 workshop. Their original plan to use the Blue Waters training allocation wasn't ideal for a short workshop for ET (requires students to use SSH, system editors; can't easily run Jupyter; IO is slow for compilation; must submit jobs, etc.
- 7/21: Gave access to existing pi4 instance with basic Jupyter notebook with ET dependencies.
- Response: IO is slow (compiling comparable to BW) due to use of Gluster FS. Much slower than single-node Jupyterhub. Will either use BW (if issues solved) or Jupyterhub.
- 7/21: Setup single-node instance of Workbench (32core/96G) on Nebula for performance comparison.
- 7/24: Received message from co-organizer requesting changes to the Docker image
- Default python2 interpreter for terminal, but support python3 notebook.
- Fix RequestEntityTooLarge errer (nginx max body size)
- Question about whether all students would be on a single VM or multiple
- Additional packages: numactl-devel numactl hwloc hwloc-devel openssl-devel hdf5 hdf5-devel gdb
- 7/25: Requested gdb and gsl
- 7/26: Requested 64core VM
- 7/28: Instructors began testing whether the image/environment works for their tutorials
- Requested additional dependencies in image
- 7/31:
- 9am: School starts
- 30+ people in room
- ~4 issues with Safari – but this is with Jupyter, not Workbench. Couldn't get terminal and invalid kernel
- Issues cloning git repo (usually typos)
- Note: Lots of tension when things don't work as expected.
- Note: Logging in twice is annoying for most users
- 10am. Back to the office
- 11am: All's quiet. ~36 jupyter instances running on single node. Load average ~1.
- 15-50 accounts (encourage groups of 3)
- Custom Jupyter notebook with ET dependencies
- 2 core, 2GB RAM, 5GB disk per user
- Pre-loaded data
- Workload: