hlib
HLib is a library for hierarchical matrices that was written by Lars Grasedyck and Steffen Börm. Most routines are written in the C programming language using BLAS and LAPACK for lower-level algebraic operations. The library contains functions for H- and H2-matrix arithmetics, the treatment of partial differential equations and a number of integral operators as well as support routines for the creation of cluster trees, visualization and numerical quadrature. This is a work in progress, so there may be undiscovered errors and you can expect new features to appear with every new release.
Keywords for this software
References in zbMATH (referenced in 63 articles , 1 standard article )
Showing results 1 to 20 of 63.
Sorted by year (- Ayala, Alan; Claeys, Xavier; Grigori, Laura: Linear-time CUR approximation of BEM matrices (2020)
- Dölz, Jürgen: A higher order perturbation approach for electromagnetic scattering problems on random domains (2020)
- Keßler, Torsten; Rjasanow, Sergej; Weißer, Steffen: Vlasov-Poisson system tackled by particle simulation utilizing boundary element methods (2020)
- Massei, Stefano; Robol, Leonardo; Kressner, Daniel: Hm-toolbox: MATLAB software for HODLR and HSS matrices (2020)
- Sushnikova, Daria A.; Oseledets, Ivan V.: Simple non-extensive sparsification of the hierarchical matrices (2020)
- Alger, Nick; Rao, Vishwas; Myers, Aaron; Bui-Thanh, Tan; Ghattas, Omar: Scalable Matrix-free adaptive product-convolution approximation for locally translation-invariant operators (2019)
- Boukaram, Wajih; Turkiyyah, George; Keyes, David: Randomized GPU algorithms for the construction of hierarchical matrices from matrix-vector operations (2019)
- Dölz, Jürgen; Harbrecht, Helmut; Multerer, Michael D.: On the best approximation of the hierarchical matrix product (2019)
- Dölz, Jürgen; Kurz, Stefan; Schöps, Sebastian; Wolf, Felix: Isogeometric boundary elements in electromagnetism: rigorous analysis, fast methods, and examples (2019)
- Karkulik, Michael; Melenk, Jens Markus: (\mathscrH)-matrix approximability of inverses of discretizations of the fractional Laplacian (2019)
- Kressner, Daniel; Massei, Stefano; Robol, Leonardo: Low-rank updates and a divide-and-conquer method for linear matrix equations (2019)
- Shepherd, David; Miles, James; Heil, Matthias; Mihajlović, Milan: An adaptive step implicit midpoint rule for the time integration of Newton’s linearisations of non-linear problems with applications in micromagnetics (2019)
- Börm, Steffen: Adaptive compression of large vectors (2018)
- Dölz, Jürgen; Harbrecht, Helmut: Hierarchical matrix approximation for the uncertainty quantification of potentials on random domains (2018)
- Feischl, Michael; Kuo, Frances Y.; Sloan, Ian H.: Fast random field generation with (H)-matrices (2018)
- Xing, Xin; Chow, Edmond: Preserving positive definiteness in hierarchically semiseparable matrix approximations (2018)
- Betcke, Timo; van’t Wout, Elwin; Gélat, Pierre: Computationally efficient boundary element methods for high-frequency Helmholtz problems in unbounded domains (2017)
- Börm, Steffen; Melenk, Jens M.: Approximation of the high-frequency Helmholtz kernel by nested directional interpolation: error analysis (2017)
- Chávez, Gustavo; Turkiyyah, George; Keyes, David E.: A direct elliptic solver based on hierarchically low-rank Schur complements (2017)
- Corona, Eduardo; Rahimian, Abtin; Zorin, Denis: A tensor-train accelerated solver for integral equations in complex geometries (2017)
Further publications can be found at: http://www.hmatrix.org/literature.html