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MFEM
The open-source MFEM library enables application scientists to quickly prototype parallel physics application codes based on PDEs discretized with high-order finite elements.

ETHOS
The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms.

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.

Robert Stephany
As Computing’s eighth Fernbach Fellow, postdoctoral researcher Robert Stephany will develop specialized algorithms under the mentorship of Youngsoo Choi.

Tarik Dzanic
As Computing’s seventh Fernbach Fellow, postdoctoral researcher Tarik Dzanic will develop new algorithms and test them in computational physics simulations under the mentorship of Bob Anderson.

Andrew Gillette
CASC computational mathematician Andrew Gillette has always been drawn to mathematics and says it’s about more than just crunching numbers.

Mapping cosmic shear to illuminate dark energy
In a recent study published in the Astrophysical Journal, LLNL researchers developed an innovative approach to map cosmic shear using linear algebra, statistics, and HPC.

High-performance computing at a crossroads
LLNL's Bruce Hendrickson joins other HPC luminaries in this op-ed about the future of the field.

S&TR cover story: Beginning at the end
The DarkStar inverse design technique blends AI, machine learning, and advanced hydrodynamics simulations to optimize science and engineering solutions starting from the final state.