collaborators

5 papers

cs.DC2026

Application Failures and Machine Computational Efficiency

Carlo Graziani, Bethany Lusch, O. E. Bronson Messer

We present a framework for evaluating uptime efficiency of Exascale-class scientific computers when application failure rates are appreciable. This is the situation that confronts…

cs.DC2026

A Scalable Pattern Mining Workflow for Interpretable Machine Log Analysis in High-Performance Computing Environments

Shilpika Shilpika, Bethany Lusch, Eric Pershey +3

Modern supercomputers housed in High Performance Computing (HPC) environments generate massive volumes of log data daily, revealing intricate information and performance metrics ab…

cs.CL2026

Probabilistic Attribution For Large Language Models

Shilpika Shilpika, Carlo Graziani, Bethany Lusch +2

The generative nature of Large Language Models (LLMs) is reflected in the conditional probabilities they compute to sample each response token given the previous tokens. These prob…

physics.flu-dyn2025

Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks

Shivam Barwey, Pinaki Pal, Saumil Patel +5

A graph neural network (GNN) approach is introduced in this work which enables mesh-based three-dimensional super-resolution of fluid flows. In this framework, the GNN is designed…

cs.DC2025

An Incremental Multi-Level, Multi-Scale Approach to Assessment of Multifidelity HPC Systems

Shilpika Shilpika, Bethany Lusch, Venkatram Vishwanath +1

With the growing complexity in architecture and the size of large-scale computing systems, monitoring and analyzing system behavior and events has become daunting. Monitoring data…