High-Performance Computing Simulation and Data Science

Project Highlights

 
FY2021

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 FY21 projects in other research categories.

Project Title Project Code Principal Investigator Project Type Project Status
Automated Software Integration 21-SI-005 George Todd Gamblin Strategic Initiative Continuing
Robust Control of Scientific Simulations with Deep Reinforcement Learning 21-SI-001 Daniel Faissol Strategic Initiative Continuing
Efficient Reduced-Order Models for Multi-Physics Simulations 21-FS-042 Youngsoo Choi Feasibility Study Final
Scalable Motif-Driven Parallel Generative Adversarial Net for Community Detection 21-FS-029 Byung Yoo Feasibility Study Final
Using a Compressed Format for Floating-Point Data as a Data Type to Create Adaptive-Precision Compressed Arrays 21-FS-028 Alyson Fox Feasibility Study Final
The Applicability of Unit Systems to High-Performance Computing Applications 21-FS-016 Tristan Vanderbruggen Feasibility Study Final
Learning a Nonlinear Solver Optimized to Solve the Problem of Electron Density and Effective Atomic Number Reconstruction 21-FS-013 Kadri Aditya Mohan Feasibility Study Continuing
Reliable Linear Solvers in Unreliable Computing Environments 21-FS-007 Christopher Vogl Feasibility Study Final
Scientific Machine Learning at Extreme Scale: Optimal Control for Deep Learning in High-Performance Computing 21-ERD-051 Stefanie Guenther Exploratory Research Continuing
An Experimentally Validated Synergistic Membrane Model 21-ERD-047 Timothy Carpenter Exploratory Research Continuing
Exact Representation of Curved Material Interfaces and Boundaries in High-Order Finite Element Simulations 21-ERD-031 Vladimir Tomov Exploratory Research Continuing
DENAS: Deep Neuroevolution at Scale 21-ERD-026 Samson Jacobs Exploratory Research Continuing
Cross-Scale Modeling for Component Scale Simulations 21-ERD-022 Matthew Nelms Exploratory Research Continuing
Interactive Exploratory Graph-Enabled Data Analytics at High-Performance Computing Scales 21-ERD-020 Roger Pearce Exploratory Research Continuing
Achieving Peak Performance of High-Performance Computing Applications by Optimizing Parallelism Compilation 21-ERD-018 Giorgis Georgakoudis Exploratory Research Continuing
Knowledge-Driven Machine Learning 21-ERD-012 Jayaraman Jayaraman Thiagarajan Exploratory Research Continuing
Decentralized Autonomous Networks for Cooperative Estimation 20-SI-005 Ryan Goldhahn Strategic Initiative Continuing
Machine Learning-Driven Dynamic Four-Dimensional X-Ray Computed Tomography Reconstruction 20-FS-010 Hyojin Kim Feasibility Study Final
Probabilistic Models for Dynamic Hypergraphs with Content 20-ERD-049 Grant Boquet Exploratory Research Continuing
Approximate High-Performance Computing: A Fast and Energy-Efficient Computing Paradigm in the Post-Moore Era 20-ERD-043 Harshitha Gopalakrishnan Menon Exploratory Research Continuing