7 papers
Quantifying the Impact of Lossy Compression on Neural Generative Surrogate Modeling
Zhimin Li, Harshitha Menon, Charles Jekel +2
Neural networks are used as generative surrogate models for scientific discovery, which are trainable approximations of scientific simulations. These models enable users to replace…
Understanding and Improving Communication Performance in Multi-node LLM Inference
Prajwal Singhania, Siddharth Singh, Lannie Dalton Hough +4
As large language models (LLMs) continue to grow in size, distributed inference has become increasingly important. Model-parallel strategies must now efficiently scale not only acr…
Multi-Agent Collaboration for Automated Design Exploration on High Performance Computing Systems
Harshitha Menon, Charles F. Jekel, Kevin Korner +15
Today's scientific challenges, from climate modeling to Inertial Confinement Fusion design to novel material design, require exploring huge design spaces. In order to enable high-i…
Passive freeze-out of the Richtmyer-Meshkov instability
J. Strucka, D. M. Sterbentz, B. Lukic +16
The Richtmyer-Meshkov instability (RMI) poses a major challenge in inertial confinement fusion (ICF) due to its role in mixing and performance degradation. We report the first expe…
Optimizing Agentic Language Model Inference via Speculative Tool Calls
Daniel Nichols, Prajwal Singhania, Charles Jekel +2
Language models (LMs) are becoming increasingly dependent on external tools. LM-based agentic frameworks frequently interact with their environment via such tools to search files,…
Multi-Agent Design Assistant for the Simulation of Inertial Fusion Energy
Meir H. Shachar, Dane M. Sterbentz, Harshitha Menon +10
Inertial fusion energy promises nearly unlimited, clean power if it can be achieved. However, the design and engineering of fusion systems requires controlling and manipulating mat…