Linear Algebra Primary Contact: Jack Dongarra (dongarra@cs.utk.edu)

Jack Dongarra (Project Director), Susan Blackford, Henri Casanova, Andy Cleary, Brett Ellis, Graham Fagg, Eric Grimme, Sven Hammarling, Ed Hayes, Rich Lehoucq, Aurelio Oliviera, Antone Petitet, Marielba Rojas, Sandra Santos, Danny Sorensen, Zdenko Tomasic, Yves Robert, Paul Van Dooren, Clint Whaley, Chao Yang, and Wei Zuo.

Abstract. Several areas in linear algebra must be addressed to allow wide use of parallel computing. These areas include the development of software libraries for distributed-memory machines, dense nonsymmetric eigenvalue problems, parallel algorithms for large-scale eigenvalue problems, sparse linear least squares, multigrid algorithms, sparse linear systems, and linear algebra for signal processing.  

Corporate Sponsors for this research area are currently not available.

• ARPACK - Eigenvalues and eigenvectors for large, sparse, or structured matrices.

• Parallel ARPACK - A parallel version ARPACK, a collection of Fortran 77 subroutines designed to solve large scale eigenvalue problems.

• LAPACK: Linear Algebra Package - A set of routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems.

• NetSolve - A network-based computational server that allows users to access computational resources, such as hardware and software, distributed across the network.

• PVMPI - An integration of the PVM and MPI systems.

• ScaLAPACK: Scalable Linear Algebra Package - A set of routines for the solution of linear systems of equations.
  • An HPF Implementation of ScaLAPACK

• Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods