symPACK Sparse Symmetric Direct Solver
We developed and a new direct linear solver for sparse symmetric positive definite matrices, symPACK. By exploiting the symmetry explicitly, symPACK achieves low storage costs.
SuperLU Sparse Unsymmetric Direct Solver
The recently developed communication-avoiding 3D sparse LU factorization in SuperLU_DIST reduces latency, achieving speedups up to 27x for planar graphs and up to 2.5x for non-planar graphs over the b...
Sparse Low-rank Hierarchical Matrix Preconditioner
STRUMPACK (STRUctured Matrices PACKage) software uses faster algorithms developed in SSG using hierarchical low-rank matrix algebra, which generalizes fast multipole methods and leads to factorization...
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 solvers and preconditions
- Multigrid methods
- Sparse eigensolvers
- Optimization, machine learning
- Communication-avoiding algorithms (see, e.g., http://bebop.cs.berkeley.edu/)
- Mathematical software
Group Leader: X. Sherry Li
Currently we do not have openings.