symPACK Sparse Symmetric Direct Solver
SuperLU Sparse Unsymmetric Direct Solver
Sparse Low-rank Hierarchical Matrix Preconditioner
Solvers for Edge Plasma Simulation
High Performance Geometric Multigrid
Accelerating Eigenpair Computations
Develop efficient linear and eigensolver algorithms and fast, scalable, library implementations. Integrate the new algorithms and software into DOE applications.
Current expertise in SSG includes:
- Dense linear algebra
- Factorization-based sparse linear solvers
- Multigrid methods
- Sparse eigensolvers
- Communication-avoiding algorithms (see, e.g., http://bebop.cs.berkeley.edu/)
- Mathematical software and libraries
Group Leader: X. Sherry Li
Roel Van Beeumen won one of two best poster blitz prizes at the Householder Symposium XX on Numerical Linear Algebra at Virginia Tech, June 18-23, 2017.
Congratulations to Mathias Jacquelin whose joint paper with Bert De Jong (CCMC), Eric Bylaska (PNNL), Jeff Hammond, and Michael Klemm (Intel),“Performance Evaluation of NWChem Ab-Initio Molecular Dynamics (AIMD) Simulations on the Intel Xeon Phi Processor” has been given the “Best Paper Award” at the IXPUG workshop held in conjunction with the ISC 2017 conference.
Lin Lin has been honored with a 2017 SIAM Activity Group on Computational Science and Engineering (SIAG/CSE) Early Career Prize.