SDSC Summer Institute 2023 website: https://na.eventscloud.com/website/54186/
This repository hosts all material and slides of the presentations at the Summer Institute
- A full catalog of all our trainings at SDSC can be found here.
For your convenience, we’ve create aliases and symlinks for the Summer Institute
- srun-shared - start an interactive session on a shared compute node
- srun-compute – start an interactive session on a compute node
- srun-gpu-shared – start an interactive session on one GPU
- jupyter-shared-spark – start a JupyteLab session for Spark on a shared compute node
- jupyter-compute-tensorflow – start a JupyterLab session for TensorFlow session on a compute node
- jupyter-gpu-shared-tensorflow – start a JupyterLab session for TensorFlow on one GPU
- data – symlink to staged data In the event that you need to explicitly use the reservation, training accounts will have access to SI2021RES for duration of SI
All times are in Pacific time.
| TIME (Pacific time) | TOPIC | PRESENTER |
|---|---|---|
| 9:00 AM - 11:00 AM | 1.0 Preparation Day - Welcome & Orientation | Robert Sinkovits |
| TIME (Pacific time) | TOPIC | PRESENTER |
|---|---|---|
| 8:00 AM – 8:30 AM | Check-in & Registration | |
| 8:30 AM – 9:30 AM | Welcome | |
| 8:15 AM – 9:15 AM | 2.1 Parallel Computing Concepts | Robert Sinkovits |
| 9:30 AM - 10:15 AM | 2.2 Hardware Overview | Andreas Goetz |
| 10:15 AM – 10:30 AM | Break | |
| 10:30 AM – 12:00 PM | 2.3 Intermediate Linux | Andreas Goetz |
| 12:00 PM - 1:30 PM | Lunch | |
| 1:30 PM – 2:30 PM | 2.4 Batch Computing | Mary Thomas |
| 2:30 PM – 2:45 PM | Break | |
| 9:00 AM – 10:00 AM | 2.5 Interactive Computing | Mary Thomas |
| 4:15 PM | Q&A + Wrap-up | |
| 4:30 PM - 6:30 PM | Reception |
| TIME (Pacific time) | TOPIC | PRESENTER |
|---|---|---|
| 8:00 AM – 8:30 AM | Check-in & Light Breakfast | |
| 8:30 AM – 9:00 AM | 3.1 Security | Nicole Wolter |
| 9:00 AM – 10:00 AM | 3.2 Data Management | Marty Kandes |
| 10:00 AM – 10:15 AM | Break | |
| 10:15 AM – 11:00 AM | 3.3 Getting Help | Nicole Wolter |
| 11:00 AM – 12:00 PM | 3.4 Code Migration | Mahidhar Tatineni |
| 12:00 PM - 1:30 PM | Lunch | |
| 1:30 PM – 2:45 PM | 3.5 High Throughput Computing | Marty Kandes |
| 2:45 PM - 3:00 PM | Break | |
| 3:00 PM - 4:30 PM | 3.6 Linux Tools for File Processing | Robert Sinkovits |
| 4:30 PM | Q&A + Wrap-up |
| TIME (Pacific time) | TOPIC | PRESENTER |
|---|---|---|
| 8:00 AM – 8:30 AM | Check-in & Light Breakfast | |
| 8:30 AM – 10:00 AM | 4.1a Intro to Git & GitHub | Mahidhar Tatineni |
| 8:30 AM – 10:00 AM | 4.1b Advanced Git & GitHub | Marty Kandes |
| 10:00 AM – 10:15 AM | Break | |
| 10:15 AM – 12:30 PM | 4.2a Python for HPC | Andrea Zonca |
| 10:15 AM – 12:30 PM | 4.2b Information Visualization Concepts | Neil Smith |
| 12:30 PM - 2:00 PM | Lunch | |
| 2:00 PM – 4:30 PM | 4.3a Scientific Visualization for mesh based data with Unreal Engine 5 | Neil Smith |
| 2:00 PM – 4:30 PM | 4.3b Scalable Machine Learning | Mai Nguyen Paul Rodriguez |
| 4:30 PM | Q&A + Wrap-up |
| TIME (Pacific time) | TOPIC | PRESENTER |
|---|---|---|
| 8:00 AM – 8:30 AM | Check-in & Light Breakfast | |
| 8:30 AM – 11:00 AM | 5.1a Performance Tuning | Robert Sinkovits |
| 8:30 AM – 11:00 AM | 5.1b Deep Learning - Part 1 | Mai Nguyen Paul Rodriguez |
| 11:00 AM – 11:15 AM | Break | |
| 11:15 AM - 12:15 PM | 5.3 An Introduction to Singularity: Containers for Scientific and High-Performance Computing | Marty Kandes |
| 12:15 PM – 1:45 PM | Lunch | |
| 1:45 PM – 4:30 PM | 5.2a GPU Computing and Programming | Andreas Goetz |
| 1:45 PM – 4:30 PM | 5.2b Deep Learning – Part 2 | Mai Nguyen Paul Rodriguez |
| 4:30 PM | Q&A + Wrap-up | |
| 6:00 PM - 8:00 PM | Evening Dinner |
| TIME (Pacific time) | TOPIC | PRESENTER |
|---|---|---|
| 8:00 AM – 8:30 AM | Check-in & Light Breakfast | |
| 8:30 AM – 11:30 AM | 6.1a Parallel Computing using MPI & Open MP | Mahidhar Tatineni |
| 8:30 AM – 11:30 AM | 6.1b A Short Introduction to Data Science and its Applications | Ilkay Altintas Subhasis Dasgupta Shweta Purawat |
| 11:30 AM – 12:15 PM | 6.2 Scaling up Interactive Data Analysis in Jupyter Lab: From Laptop to HPC | Peter Rose |
| 12:15 PM – 12:30 PM | Closing Remarks | Robert Sinkovits |
The Voyager supercomputer is an innovative AI system designed specifically for science and engineering research at scale. Funded by the National Science Foundation, Voyager represents a collaboration with the San Diego Supercomputer Center at UC San Diego, Supermicro, and Intel’s Habana Lab focused on supporting research in science and engineering that is increasingly dependent upon artificial intelligence and deep learning as a critical element in the experimental and/or computational work.
- Voyager: Exploring Habana processor-based AI focused hardware for Science and Engineering Training Session
- Voyager User Guide HERE.
- Voyager video HERE.
CoudBank is a managed service to simplify cloud access for computer science research. CloudBank overview video HERE. DCL funding opportunity for PIs who have existing CISE awards, details HERE.
SeedMe is a scientific data management framework for teams struggling with intractable data.
SeedMeLab overview talk HERE.
All the teaching material in this repository is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
If you are re-using this material, please cite our record on Zenodo