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.
Yang Liu received the Sergei A. Schelkunoff Transactions Prize Paper Award given by the IEEE Antennas and Propagation Society, for the following paper: Han Guo, Yang Liu, Jun Hu, and Eric Michielssen, "A Butterfly-Based Direct Integral-Equation Solver Using Hierarchical LU Factorization for Analyzing Scattering From Electrically Large Conducting Objects", IEEE Transactions on Antennas and Propagation 65, no. 9 (2017): pages 4742-4750, September 2017. See more details here: https://www.ieeeaps.org/awards/ieee-and-ap-s-awards/2018-ap-s-award-recipients
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.