Careers | Phone Book | A - Z Index



The recently developed HipGISAXS software is an unique massively parallel code to simulate and analyze custom and complex morphologies from Grazing Incidence Small Angle X-ray Scattering (GISAXS) experiments characterizing the nanostructural features of materials, particularly at surfaces and interfaces. Using C++ augmented with MPI, Nvidia CUDA, OpenMP, and parallel-HDF5 libraries on large-scale clusters of multicores and GPUs

Accelerating Eigenpair Computations


Novel approach developed by SciDAC FASTMath Institute accelerates computations of large numbers of extreme eigenpairs of Hermitian operators. The new eigenvalue solver has been tested in the framework of Quantum Espresso codes for electronic structure calculations. Current experimental parallel implementations show a 2x speedup over existing state-of-the-art methods. Ongoing work will be on further advancement of scalability of the algorithm.

Solvers for Edge Plasma Simulation


Researchers in the Scalable Solvers Group at LBNL help the SciDAC application partnership Center for Edge Plasma Simulation (EPSI) by developing solvers for advanced fusion simulation codes based upon first-principles physical modes in realistic magnetic separatrix geometry, to provide insight into multi-physics in the edge region of tokamak reactors and their nonlocal interaction with core plasma dynamics.

High Performance Geometric Multigrid

Screen Shot 2015 03 04 at 3.30.54 PM

Research scientists at LBNL and Argonne National Laboratory have developed a new high performance computing metric intended to provide the community with both a ranking metric for the worlds largest general purpose computers and a simple, compact, standalone benchmark that pressures machines in a balanced way to proxy modern application and their scaling demands.

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 linear solvers
  • multigrid methods
  • sparse eigensolvers
  • optimization
  • communication-avoiding algorithms -- see, e.g.,
  • mathematical software and libraries

Group Leader:  X. Sherry Li

March 2017: News

Lin Lin has ben honored with a 2017 SIAM Activity Group on Computational Science and Engineering (SIAG/CSE) Early Career Prize.

April 2016: News

The SSG group has a strong show in the SIAM Conf. on Parallel Processing, April 12-15, 2016. Pieter Ghysels, Mathias Jacquelin, and Chao Yang will all give presentations on new research results in linear solvers and eigensolvers. 

March 2016: News

Sherry Li has been named a 2016 fellow of the SIAM.

December 2015: News

* Congratulations to SSG senior staff scientist Sherry Li who has been elected to the SIAM Council.

November 2015: News

* Congratulations to SSG faculty scientist Jim Demmel who is among 347 new fellows named to the American Association for the Advancement of Science.  Demmel was cited for his distinguished contributions to the theory and practice of numerical linear algebra, especially for innovative approaches in parallel computing.

October 2015: News

* DMML Workshop Dedicated to James Demmel

The Development of Modern Methods for Linear Algebra (DMML) workshop held October 23 - 24 at UC Berkeley was dedicated to SSG Faculty Scientist James Demmel for his leadership in modern high-accuracy and high-performance linear algebra solvers and for his promotion of numerical linear algebra to a broad audience through software, teaching, and collaboration.

Xiaoye (Sherry) Li helped organize the workshop and Deputy Lab Director Horst Simon is among the confirmed speakers

June 2015: News

* Congratulations to Sherry Li whose joint paper with Brian Austin and Eric Roman, "Resilient Matrix Multiplication of Hierarchical Semi-Separable Matrices," was just given the "FTXS 2015 Best Paper Award."

April 2015: News

* Congratulations to SSG faculty scientist Jim Demmel who was just awarded the ACM Paris Kanellakis Theory and Practice Award for his work on numerical linear algebra libraries, including LAPACK.