PROJECTS
Topological Analysis
LLNL and University of Utah researchers have developed an advanced, intuitive method for analyzing and visualizing complex data sets.
Legacy
NSDE
The NSDE project is focused on research and development of nonlinear solvers and sensitivity analysis techniques for nonlinear, time-dependent, and steady-state partial differential equations.
PSUADE
The flourishing of simulation-based scientific discovery has also resulted in the emergence of the UQ discipline, which is essential for validating and verifying computer models.
NEWS
LLNL uses ML to derive black hole motion from gravitational waves
An LLNL mathematician and collaborators have developed a machine learning–based technique capable of deriving a mathematical model for the motion of binary black holes from gravitational wave data.
Using supercomputers to optimize hot rolling for the steels of tomorrow
In a project with U.S. Steel, LLNL computational physicists built models of the hot-rolling process to run on LLNL’s HPC platforms.
Inaugural industry forum inspires ML community
LLNL held its first-ever Machine Learning for Industry Forum (ML4I) on August 10–12, co-hosted by the Lab’s High-Performance Computing Innovation Center and Data Science Institute.