## 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…

## Our Mission

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

## Position openings

- HPC postdoc (PI: Mark Adams)

96766: https://lbl.taleo.net/careersection/2/jobdetail.ftl?lang=en&job=96766

- Quantum algorithms postdoc (PI: Roel Van Beeumen)

96681: https://lbl.taleo.net/careersection/2/jobdetail.ftl?lang=en&job=96681

- Plasma simulation and ML postdoc (PI: Yang Liu)

96330: https://lbl.taleo.net/careersection/2/jobdetail.ftl?lang=en&job=96330