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Center for Applied Scientific Computing

Scientific Computing Group

Members of the Scientific Computing Group develop new and efficient numerical algorithms, techniques, and methodologies for solving scientific applications on high-performance computing systems. Our research is in a spectrum of areas of vital interest to LLNL, and we work in close collaboration with Laboratory programs and other national laboratories and universities. Areas of current interest/expertise include multi-physics and multi-scale modeling, climate modeling, subsurface flow modeling, structured adaptive mesh refinement (SAMRAI), mathematical and computational biology, computational fluid dynamics, ALE-AMR techniques, high-order discretizations, first-principles molecular dynamics, quantum Monte Carlo, plasma modeling for both ICF and magnetic fusion, nonlinear systems and solvers, verification, object-oriented software design, and algorithm performance on next-generation computing architectures.

To learn more about what we do, we invite you to look at some of the projects to which our group members contribute: Climate Modeling, Edge Plasmas, Kinetics of Phase Evolution, Qbox: Massively-Parallel First Principles Molecular Dynamics, Linear Scaling Electronic Structure Calculations, Structured Adaptive Mesh Refinement (SAMRAI), ARES-AMR Applications, Sundials, Extreme Resilient Discretizations, and the Extreme Materials at Extreme Scale Co-Design Center

Group Lead

Jeff Hittinger: hydrodynamics, computational physics, adaptive mesh refinement, verification, uncertainty quantification

Research Staff

Robert Anderson: hydrodynamics, computational physics, adaptive mesh refinement

Milo Dorr: scientific computing, numerical analysis, parallel processing, plasma models, multigrid methods

Erik Draeger: first-principles material simulations, density functional theory, Quantum Monte Carlo, molecular dynamics, massively parallel computing

Jean-Luc Fattebert: first-principles molecular dynamics algorithms, large scale eigenvalue problems, parallel scientific computing, phase-field modeling

David Gardner: multi-scale modeling, implicit-explicit time integration, nonlinear solvers, parallel computing

Brian Gunney: adaptive mesh refinement, high-performance computing, numerical methods for partial differential equations, computational physics

Rich Hornung: numerical methods for partial differential equations, multiscale methods for gas dynamics, adaptive mesh refinement, parallel scientific computing, object-oriented software design, flow in porous media

John Loffeld: exponential integrators, numerical analysis, parallel computing, object-oriented software design

Daniel Osei-Kuffuor: preconditioning techniques for highly indefinite linear systems

Amanda Randles: high performance computing, computational fluid dynamics, modeling physical/biological phenonema and systems

Steve Smith: object-oriented software design, adaptive mesh refinement, subsurface modeling

Liam Stanton: continuum modeling and nonlinear dynamics in materials science, electrochemistry and plasmas

Tanya Vassilevska: mathematical and computational biology

Carol Woodward: nonlinear solvers, implicit PDE methods, verification, parallel computing, flow through porous media, numerical error estimation