66 citations · 89 across the 14 of their papers we have counts for
14 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…
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,…
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 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…
Integrating Performance Tools in Model Reasoning for GPU Kernel Optimization
Daniel Nichols, Konstantinos Parasyris, Charles Jekel +2
Language models are now prevalent in software engineering with many developers using them to automate tasks and accelerate their development. While language models have been tremen…
Explosively driven Richtmyer--Meshkov instability jet suppression and enhancement via coupling machine learning and additive manufacturing
Dane M. Sterbentz, Dylan J. Kline, Daniel A. White +10
The ability to control the behavior of fluid instabilities at material interfaces, such as the shock-driven Richtmyer--Meshkov instability, is a grand technological challenge with…
Using Conservation Laws to Infer Deep Learning Model Accuracy of Richtmyer-meshkov Instabilities
Charles F. Jekel, Dane M. Sterbentz, Sylvie Aubry +3
Richtmyer-Meshkov Instability (RMI) is a complicated phenomenon that occurs when a shockwave passes through a perturbed interface. Over a thousand hydrodynamic simulations were per…
Neural Network Layers for Prediction of Positive Definite Elastic Stiffness Tensors
Charles F. Jekel, Kenneth E. Swartz, Daniel A. White +2
Machine learning models can be used to predict physical quantities like homogenized elasticity stiffness tensors, which must always be symmetric positive definite (SPD) based on co…
Testing Surrogate-Based Optimization with the Fortified Branin-Hoo Extended to Four Dimensions
Charles F. Jekel, Raphael T. Haftka
Some popular functions used to test global optimization algorithms have multiple local optima, all with the same value, making them all global optima. It is easy to make them more…
Computational Design of Microarchitected Flow-Through Electrodes for Energy Storage
Victor A. Beck, Jonathan J. Wong, Charles F. Jekel +4
Porous flow-through electrodes are used as the core reactive component across electrochemical technologies. Controlling the fluid flow, species transport, and reactive environment…
Fortified Test Functions for Global Optimization and the Power of Multiple Runs
Charles F. Jekel, Raphael T. Haftka
Some popular functions used to test global optimization algorithms have multiple local optima, all with the same value. That is all local optima are also global optima. This paper…
Classifying Online Dating Profiles on Tinder using FaceNet Facial Embeddings
Charles F Jekel, Raphael T. Haftka
A method to produce personalized classification models to automatically review online dating profiles on Tinder is proposed, based on the user's historical preference. The method t…