H2Opus: a Performance-Oriented Library for Hierarchical Matrices
About
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.
