#### 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.

#### 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.

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#### 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.

#### A winning strategy for deep neural networks

LLNL continues to make an impact at top machine learning (ML) conferences, even as much of the research staff works remotely during the COVID-19 pandemic.

#### S&TR cover story: The exascale software portfolio

The latest issue of LLNL's *Science & Technology Review* magazine showcases Computing in the cover story alongside a commentary by Bruce Hendrickson.