ALCF DeepHyper Automated Machine Learning Workshop
Argonne National Laboratory
July 15, 2022
The Argonne Leadership Computing Facility (ALCF) will host a hands-on training session on DeepHyper (github.com/deephyper/deephyper), a distributed automated machine learning (AutoML) software package for automating the design and development of deep neural networks for scientific and engineering applications.
DeepHyper seeks to bring a scientifically rigorous automated approach to neural network model development by reducing the manually intensive, cumbersome, ad hoc, trial-and-error efforts.
DeepHyper can run on a laptop, medium range clusters, and supercomputers with thousands of compute units (GPUs).
Nesar Soorve Ramachandra
Akhil Pandey Akella
In this virtual workshop attendees will learn various capabilities of the DeepHyper software to automate the design and development of neural networks.
- Workshop repo: github.com/deephyper/anl-22-summer-workshop
- DeepHyper GitHub repo: github.com/deephyper/deephyper
- DeepHyper Documentation: deephyper.readthedocs.io
All times are Central Standard Time (CDT)
- 8:30 – 9:00: Checkin and setup
- 9:00 – 9:10: Welcome & Intro (Prasanna Balaprakash) [Slides][Video]
- 9:10 – 9:30: Hyperparameter search (Prasanna Balaprakash) [Slides][Video]
- 9:30 – 10:00: Hands-on (Romain Egele) [Video]
- 10:00 – 10:20: Neural architecture search (Romit Maulik) [Slides][Video]
- 10:20 – 10:50: Hands-on (Romit Maulik) [Video]
- 11:00 – 11:20: Ensembles & uncertainty quantification (Bethany Lusch and Krishnan Raghavan) [Slides][Video]
- 11:20 – 11:50: Hands-on (Bethany Lusch and Krishnan Raghavan) [Video]
- 12:30 – 12:50: Transfer learning in hyperparameter search (Sandeep Madireddy and Tanwi Mallick) [Slides][Video]
- 12:50 – 1:20: Hands-on (Sandeep Madireddy and Tanwi Mallick) [Video]
- 1:20 – 2:10: Running DeepHyper at Scale (No handson; only demo)[Video]
Part 4 - Latest Research
- 2:20 – 2:40: Multiobjective hyperparameter search (Anirudh Subramanyam) [Slides] [Video]
- 2:40 – 3:10: Hands-on (Anirudh Subramanyam) [Video]
- 3:10 – 3:30: Graph neural architecture search for molecular property prediction (Akhil Pandey Akella) [Slides][Video]
- 3:30 – 4:00: Hands-on (Akhil Pandey Akella) [Video]