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  4. hm-toolbox: MATLAB SOFTWARE FOR HODLR AND HSS MATRICES
 
research article

hm-toolbox: MATLAB SOFTWARE FOR HODLR AND HSS MATRICES

Massei, Stefano  
•
Robol, Leonardo
•
Kressner, Daniel  
January 1, 2020
Siam Journal On Scientific Computing

Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versatile tool to develop fast algorithms for addressing large-scale problems. While existing software packages for such matrices often focus on linear systems, their scope of applications is in fact much wider and includes, for example, matrix functions and eigenvalue problems. In this work, we present a new MATLAB toolbox called hm-toolbox, which encompasses this versatility with a broad set of tools for HODLR and HSS matrices, unmatched by existing software. While mostly based on algorithms that can be found in the literature, our toolbox also contains a few new algorithms as well as novel auxiliary functions. Being entirely based on MATLAB, our implementation does not strive for optimal performance. Nevertheless, it maintains the favorable complexity of hierarchical low-rank matrices and offers, at the same time, a convenient way of prototyping and experimenting with algorithms. A number of applications illustrate the use of the hm-toolbox.

  • Details
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Type
research article
DOI
10.1137/19M1288048
Web of Science ID

WOS:000551251700039

Author(s)
Massei, Stefano  
•
Robol, Leonardo
•
Kressner, Daniel  
Date Issued

2020-01-01

Publisher

SIAM PUBLICATIONS

Published in
Siam Journal On Scientific Computing
Volume

42

Issue

2

Start page

C43

End page

C68

Subjects

Mathematics, Applied

•

Mathematics

•

hodlr matrices

•

hss matrices

•

hierarchical matrices

•

matlab

•

low-rank approximation

•

fast algorithms

•

low-rank

•

spectral projectors

•

linear-systems

•

conquer method

•

decay bounds

•

approximation

•

superfast

•

existence

•

solver

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
ANCHP  
Available on Infoscience
August 8, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/170676
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