H2Opus: a Performance-Oriented Library for Hierarchical Matrices

H2Opus: a Performance-Oriented Library for Hierarchical Matrices

Download at https://github.com/ecrc/h2opus.

Experience our latest HPC software release that implements H²-Matrix operations on shared-memory systems, possibly equipped with GPU hardware accelerators. The prime target applications for H2Opus are PDE-constrained optimizations. 

The features of H2Opus include:

• Generation of matrix structure from a point set and admissibility condition,
• Construction of a hierarchical matrix given a kernel function,
• Matrix-vector and matrix-multiple-vector multiplication,
• Basis orthogonalization,
• Algebraic compression,
• Low rank update, and many more.

Watch the talk given by Prof. David Keyes at the E-NLA seminar here.