The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: ACM Student Research Competition, Undergraduate
Author: Thomas Papka (Loyola University Chicago, Argonne National Laboratory (ANL))
Supervisor: Venkatram Vishwanath (Argonne National Laboratory (ANL))
Abstract: Advances in artificial intelligence (AI) and machine learning (ML) are reshaping scientific computing and influencing programming practices on high performance computing (HPC) systems. We analyze Python library usage on the Polaris supercomputer to understand adoption patterns in modeling, simulation, data analysis, and ML. Using XALT, a runtime monitoring tool, and PySnooper, a lightweight tracer, we correlate library imports with job scheduler data and scientific domains. Results are presented through visualizations and an interactive dashboard, enabling scientists to track usage trends, identify performance impacts from non-optimized environments, and inform improvements to Argonne’s default Python stack. This work provides actionable guidance for software provisioning, user support, and infrastructure planning in the era of AI-driven science.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF