Members of the Scientific Computing Group develop new and efficient numerical algorithms, techniques, and methodologies for solving scientific problems 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, other groups within CASC, and other national laboratories and universities. Application areas of current interest/expertise include climate modeling, subsurface flow modeling, mathematical and computational biology, power grid simulation, computational fluid dynamics, transport models, first-principles molecular dynamics, and plasma modeling for both ICF and magnetic fusion. We actively investigate, apply, and develop new methods in multi-physics and multi-scale modeling, mathematical optimization, structured adaptive mesh refinement, ALE-AMR techniques, high-order discretizations, nonlinear systems and solvers, and variable precision computing.
To learn more about what we do, we invite you to look at some of the current projects to which our group members contribute: Climate Modeling, Linear Scaling Electronic Structure Calculations, Structured Adaptive Mesh Refinement (SAMRAI), SUNDIALS time integrators and nonlinear solvers, the Edge Simulation Laboratory, and the Variable Precision Computing Project.
Jeff Hittinger: hydrodynamics, computational plasma physics, adaptive mesh refinement, high-order finite volume methods, verification and a posteriori error estimation, variable precision computing
Robert Anderson: hydrodynamics, computational physics, adaptive mesh refinement
Bryce Campbell: hydrodynamics, multiphase flows, interface tracking schemes, numerical methods for partial differential equations, hydrodynamic stability theory, high-order numerical methods, perturbation methods for nonlinear equations
Milo Dorr: scientific computing, numerical analysis, parallel processing, plasma models, multigrid methods
David Gardner: multi-scale modeling, implicit-explicit time integration, nonlinear solvers, parallel computing
Debojyoti Ghosh: numerical methods for hyperbolic partial differential equations, finite-difference and finite-volume methods, implicit-explicit time integration, compressible flows, scalable algorithms
Matthieu Benoit Lecouvez: numerical and functional analysis, domain decomposition methods, ordinary, partial and algebraic differential equations, linear solvers
John Loffeld: exponential integrators, numerical analysis, parallel computing, object-oriented software design
Daniel Osei-Kuffuor: preconditioning techniques for highly indefinite linear systems
Slaven Peles: complex systems, differential-algebraic equations, uncertainty quantification, model verification and validation, multi-scale modeling, implicit-explicit time integration, nonlinear solvers, parallel computing
Cosmin Petra: large-scale numerical optimization, stochastic programming, parallel algorithms for the optimization of complex energy systems under uncertainty.
Claudio Santiago: combinatorial optimization, integer programming, conic programming, convex relaxations, and nonlinear programming
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
Christopher Vogl: numerical methods for partial differential equations, adaptive mesh refinement, level set methods, lipid bi-layer vesicle modeling, tsunami simulation
Carol Woodward: nonlinear solvers, implicit PDE methods, verification, parallel computing, flow through porous media, numerical error estimation