Researchers develop innovative data representations and algorithms to provide faster, more efficient ways to preserve information encoded in data.
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.
The hypre library's comprehensive suite of scalable parallel linear solvers makes large-scale scientific simulations possible by solving problems faster.
March 31, 2022
LLNL's DMTS awards program offers advancement for scientific leaders who choose the research track over the management ladder. Read more about computational mathematician Rob Falgout.
December 29, 2021
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November 12, 2021
Researchers from LLNL’s Center for Applied Scientific Computing hosted a virtual workshop on October 20 for the MFEM user and developer community.