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Scalable Solvers Group
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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.

 

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

None right now.

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