High-Performance Computing, Simulation, and Data Science

Project Highlights

 
FY2023

Click on any of the project titles below to view a brief project summary,
or return to our Project Highlights page to view lists of FY23 projects in other research categories.

Project Title Project Code Principal Investigator Project Type Project Status
Exact Representation of Curved Material Interfaces and Boundaries in High-Order Finite Element Simulations 21-ERD-031 Vladimir Tomov Exploratory Research Final
An Experimentally Validated Synergistic Membrane Model 21-ERD-047 Timothy Carpenter Exploratory Research Continuing
Accelerating Time-integrators with Surrogate Models 23-ERD-048 Steven Roberts Exploratory Research Continuing
Knowledge Extraction and Injection Via Concept-Level Reasoning in Scientific Machine Learning 23-ERD-029 Shusen Liu Exploratory Research Continuing
Multilevel Markov chain Monte Carlo Sampling Methods for Discrete Graph Problems 23-FS-008 Sarah Mackay Feasibility Study Final
Improving Extrapolation Behavior in Deep Neural Networks 22-ERD-006 Rushil Anirudh Exploratory Research Continuing
Learning to Solve Faster with Data-Driven Algebraic Multigrid Methods 23-FS-031 Ruipeng Li Feasibility Study Final
Interactive Exploratory Graph-Enabled Data Analytics at High-Performance Computing Scales 21-ERD-020 Roger Pearce Exploratory Research Final
Autonomous MultiScale: Embedded Machine Learning for Smart Simulations 22-SI-004 Peer-Timo Bremer Strategic Initiative Continuing
Designing Asynchronous Circuits for Dynamic Machine Learning Adaptation 22-DR-009 Maya Gokhale Disruptive Research Continuing
Cross-Scale Modeling for Component Scale Simulations 21-ERD-022 Matthew Nelms Exploratory Research Final
Localizing and Explaining Performance Defects in Heterogeneous Applications 23-ERD-022 Konstantinos Parasyris Exploratory Research Continuing
Large-Scale Shape Optimization with Conformal Meshes 22-ERD-023 Jorge Barrera Cruz Exploratory Research Continuing
Knowledge-Driven Machine Learning 21-ERD-012 Jayaraman Jayaraman Thiagarajan Exploratory Research Final
ForwardProp is a Novel Gradient-Free Learning Paradigm for Integrating Deep Neural Nets with Scientific Simulations 23-ERD-030 James Diffenderfer Exploratory Research Continuing
Toward the Intelligent Center for High-Performance Computing 23-ERD-045 Jae-Seung Yeom Exploratory Research Final
Next-Generation Implicit Neural Representation for Ill-Posed and Dynamic Computed Tomography Reconstruction 22-ERD-032 Hyojin Kim Exploratory Research Continuing
Achieving Peak Performance of High-Performance Computing Applications by Optimizing Parallelism Compilation 21-ERD-018 Giorgis Georgakoudis Exploratory Research Final
Automated Software Integration 21-SI-005 George Gamblin Strategic Initiative Final
Vectorization of Dynamic Subgraphs via Generative Models 23-FS-039 Geoffrey Sanders Feasibility Study Final