2019 ALCF Simulation, Data, and Learning Workshop
Held at the ALCF from October 1–3, 2019, the ALCF Simulation, Data, and Learning Workshop is intended for users getting started on ALCF computing resources, particularly with data science and machine learning applications, with near-term goals of applying for a major allocation award.
From October 1–3, 2019, we will host the ALCF Simulation, Data, and Learning Workshop to help researchers improve the performance and productivity of simulation, data science, and machine learning applications on ALCF systems. Workshop participants will have the opportunity to:
- Work directly with ALCF and industry professionals during dedicated hands-on sessions
- Learn how to use available tools and frameworks to improve productivity
- Learn how to set up workflows and use containers
- Test and debug codes with exclusive full-system reservations on ALCF systems
- Get assistance with Director's Discretionary projects to help prepare for a major allocation award
- Improve the performance of existing ALCF projects
- Plan ahead for 2020-2021 allocation proposal submissions
REGISTRATION DEADLINES
- Foreign Nationals: Friday, September 6, 2019
- U.S. Citizens: Friday, September 13, 2019
Note: Registrants will be reviewed for experience level and will be asked to provide goals for attending.
Agenda
Day 1 (Tuesday, October 1)
8:30Shuttle Departs from Guest House to TCS, Bldg. 240
9:00-9:10Welcome - Michael Papka, ANL
9:10-9:15Introduction and Safety Review - Yasaman Ghadar, ANL
9:15-10:00Getting Started with ALCF Systems - Adrian Pope, ANL
10:00-10:45Python on HPC - Taylor Childers, ANL
10:45-11:00Break
11:00-12:00Deep Learning with Keras, Tensorflow, PyTorch, and Horovod on Theta - Huihuo Zheng, ANL
12:00-12:30Overview of ADSP and Science Highlight: Deep Learning and Multimessenger Astrophysics - Elise Jennings, ANL
12:30-1:15ALCF Allocation Programs (working lunch) - Katherine Riley, ANL
1:15-2:00Parallel I/O and Storage - Kevin Harms, ANL
2:00-2:45Workflow Management with Balsam - Misha Salim, ANL
2:45-3:30DeepHyper - Prasanna Balaprakash and Romit Maulik, ANL
3:30-3:40Break
3:40-5:30Hands-on Session/Breakout Session on DeepHyper
5:30Shuttle Departs from TCS to Guest House
Day 2 (Wednesday, October 2)
8:30Shuttle Departs from Guest House to TCS, Bldg. 240
9:00-9:30Best Practices for Deep Learning for Science, Bethany Lusch, ANL
9:30-10:15
Success Stories of Science Applications Using Simulations, Machine Learning Tools and Data Science:
Ganesh Sivaraman, Ming Du, Wushi Dong
10:15-11:45TAU Performance Analysis - Nick Chaimov, Paratools
11:45-12:00Group Photo
12:00-1:00Presentations from Attendees (working lunch)
1:00-1:45Debugging and Profiling with DDT and Map - Ryan Hulguin, Arm
1:45-2:30Profiling Your Application with Intel VTune and Advisor - Paulius Velesko, Intel
2:30-3:15Using OpenMP Effectively on Theta - Ron Green, Intel
3:15-3:30Break
3:30-5:30Hands-on Session/Breakout Session Tuning Performance with OpenMP
5:30Shuttle Departs from TCS to Guest House
Day 3 (Thursday, October 3)
8:30Shuttle Departs from Guest House to TCS, Bldg. 240
9:00-9:45Using Containers on Theta - Murat Keceli, ANL
9:45-10:15Aurora Exascale System Overview, Thomas Applencourt, ANL
10:15-10:30Break
10:30-12:00Hands-On/Breakout Session Profiling Deep Learning Frameworks
12:00-1:00Presentations from Attendees (working lunch)
1:00-1:45Visualizing Your Data - Joseph Insley and Silvio Rizzi, ANL
1:45-2:15Using MPI Effectively on Theta - Sudheer Chunduri, ANL
2:15-2:30Break
2:30-3:15Getting Started with Spark on Theta - Xiao-Yong Jin, ANL
3:15-3:30Director's Discretionary (DD) Program - Yasaman Ghadar, ANL
3:30-5:00Hands-on Session
NOTE: No shuttle to Guest House. For assistance, visit registration desk.