2022 Sky Camp

Wednesday, October 19, 2022 – Banatao Auditorium, Sutardja Dai Hall, UC Berkeley Campus

Sky Camp is where you can get exposure to specific Sky Computing research projects through talks and demos, as well as hands-on experience with systems and technologies for emerging applications. This includes a new multi-region and multi-cloud data transfer service; a platform for collaborating with confidential data, privacy-preserving data analytics, and learning; a compiler for automated high-performance distributed deep learning on-top of JAX and soon PyTorch; and a new platform for running model training scripts across cloud providers.

Bookmark this page for :

Preliminary Agenda

Times listed are in PDT

  • 9:00 AM – 10:00 AM: Breakfast
  • 10:00 AM – 10:15 AM: Opening Talk: Overview of Sky Camp
  • 10:15 AM – 10:45 AM: Talk by Prof. Natacha Crooks
  • 10:45 AM – 12:00 PM: Skyplane Tutorial
  • 12:00 PM – 1:00 PM: Lunch
  • 1:00 PM – 2:30 PM: SkyPilot Tutorial
  • 2:30 PM – 2:45 PM: Break
  • 2:45 PM – 4:00 PM: Alpa Tutorial
  • 4:00 PM – 4:15 PM: Break
  • 4:15 PM – 5:30 PM: MC2 Tutorial
  • 5:30 PM – 8:00 PM: Reception

Livestream and Slack

Links to these will be provided here before the event begins.


For questions email skycamp [at] berkeley.edu


Is there parking?

We strongly encourage public transportation or ride share. However we can provide parking passes for the nearby garage, Upper Hearst Parking Structure. The garages tend to fill up by around 10:00 AM so please arrive early. If you will need a parking pass, please email us.

How can remote attendees participate?

Remote attendees can view the livestream and participate in the Sky Camp Slack conversations on the day of event. Tutorials will be supported for onsite attendees only.

How do I register?

Registration is by invite only. If you think you should have received an invitation please email us.

Prerequisites / Technical Requirements

  • “Modern” browser (Firefox, Chrome, Safari etc.)
  • Experience programming in Python in notebook environment
  • Basic understanding of AI/ML concepts (e.g., training, validation, linear models)


Some local hotel options are listed on our contact page: https://sky.cs.berkeley.edu/contact/