PROJECTS
Alkemi
Simulation workflows for ALE methods often require a manual tuning process. We are developing novel predictive analytics for simulations and an infrastructure for integration of analytics.
HYPRE
The hypre library's comprehensive suite of scalable parallel linear solvers makes large-scale scientific simulations possible by solving problems faster.
Legacy
GOLLNLP
Responding to a DOE grid optimization challenge, an LLNL-led team developed the mathematical, computational, and software components needed to solve problems of the real-world power grid.
NEWS
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.
Conference papers highlight importance of data security to machine learning
The 2021 Conference on Computer Vision and Pattern Recognition features two papers co-authored by an LLNL researcher targeted at understanding robust machine learning models.