SIAM announced its 2021 Class of Fellows, including LLNL computational mathematician Rob Falgout. Falgout is best known for his development of multigrid methods and for hypre, one of the world’s most popular parallel multigrid codes.
Our researchers will be well represented at the virtual SIAM Conference on Computational Science and Engineering (CSE21) on March 1–5. SIAM is the Society for Industrial and Applied Mathematics with an international community of more than 14,500 individual members.
SUNDIALS is a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers for initial value problems for ordinary differential equation systems, sensitivity analysis capabilities, additive Runge-Kutta methods, differential-algebraic equation systems, nonlinear algebraic systems, and more.
Lawrence Livermore National Lab has named Stefanie Guenther as Computing’s fourth Sidney Fernbach Postdoctoral Fellow in the Computing Sciences. This highly competitive fellowship is named after LLNL’s former Director of Computation and is awarded to exceptional candidates who demonstrate the potential for significant achievements in computational mathematics, computer science, data science, or scientific computing.
Alyson Fox is a math geek. She has three degrees in the subject—including a Ph.D. in Applied Mathematics from the University of Colorado at Boulder—and her passion for solving complex challenges drives her work at LLNL’s Center for Applied Scientific Computing (CASC).
Simulation workflows for Arbitrary Lagrangian–Eulerian (ALE) methods are highly complex and often require a manual tuning process. There is an urgent need to semi-automate this process to reduce user burden and improve productivity. To address this need, we are developing novel predictive analytics for simulations and an in situ infrastructure for integration of analytics. Our ongoing goals are to predict simulation failures ahead of time and proactively avoid them as much as possible.
Livermore’s hypre library of solvers makes larger, more detailed simulations possible by solving problems faster than ever before. It offers one of the most comprehensive suites of scalable parallel linear solvers available for large-scale scientific simulation.