Session
High Performance Python for Science at Scale
Session Chairs
DescriptionThis symposium-style workshop aims to connect researchers, developers, and Python practitioners to share their experiences scaling Python-based applications and workflows on supercomputers. The goal is to provide a platform for topical discussion of best practices, hands-on demonstrations, and community engagement via open-source contributions to new libraries, runtimes, and frameworks. Based on talks and demos that survey and summarize the best practices and recent success stories and developments – the workshop will serve as a requirements gathering exercise for the future of Python in HPC and science.
Event TypeWorkshop
TimeMonday, 18 November 20242pm - 5:30pm EST
LocationB304
Applications and Application Frameworks
Artificial Intelligence/Machine Learning
Parallel Programming Methods, Models, Languages and Environments
W
Presentations
| 2:00pm - 2:05pm EST | Workshop Introduction Presenter | |
| 2:05pm - 3:00pm EST | Invited Speaker Presentation Presenter | |
| 3:00pm - 3:30pm EST | High Performance Python for Science at Scale — Afternoon Break | |
| 3:30pm - 3:47pm EST | Exploring Data at Scale with Arkouda: A Practical Introduction to Scalable Data Science | |
| 3:47pm - 4:04pm EST | Work-in-progress: CUDA Python object models and parallelism models | |
| 4:04pm - 4:21pm EST | Seamlessly scale your python program from single CPU core to multi-GPU multi-node HPC cluster with cuNumeric | |
| 4:21pm - 4:38pm EST | Visualizing Workflows with the Dragon Telemetry Service | |
| 4:38pm - 4:55pm EST | Accelerating Python Applications with Dask and ProxyStore | |
| 4:55pm - 5:12pm EST | PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python | |
| 5:12pm - 5:30pm EST | Lightning Talks Presenter |