STRUMPACK -- STRUctured Matrix PACKage, Copyright (c) 2014-2021, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.
http://portal.nersc.gov/project/sparse/strumpack/master/
http://portal.nersc.gov/project/sparse/strumpack/v7.2.0/
http://portal.nersc.gov/project/sparse/strumpack/
- Pieter Ghysels - [email protected] / [email protected]
- Xiaoye S. Li - [email protected]
- Yang Liu - [email protected]
- Lisa Claus - [email protected]
- Wajih Boukaram - [email protected]
- Yotam Yaniv - [email protected]
- Henry Boateng - [email protected]
- Ryan Synk
- Lucy Guo
- Gustavo Chávez
- Liza Rebrova
- François-Henry Rouet
- Theo Mary
- Christopher Gorman
- Jonas Actor
- Michael Neuder
STRUMPACK - STRUctured Matrix PACKage - is a software library providing linear algebra routines and linear system solvers for sparse and for dense rank-structured linear systems. Many large dense matrices are rank structured, meaning they exhibit some kind of low-rank property, for instance in hierarchically defined sub-blocks. In sparse direct solvers based on LU factorization, the LU factors can often also be approximated well using rank-structured matrix compression, leading to robust preconditioners. The sparse solver in STRUMPACK can also be used as an exact direct solver, in which case it functions similarly as for instance SuperLU or superlu_dist. The STRUMPACK sparse direct solver delivers good performance and distributed memory scalability and provides excellent CUDA support.
Currently, STRUMPACK has support for the Hierarchically Semi-Separable (HSS), Block Low Rank (BLR), Hierachically Off-Diagonal Low Rank (HODLR), Butterfly and Hierarchically Off-Diagonal Butterfly (HODBF) rank-structured matrix formats. Such matrices appear in many applications, e.g., the Boundary Element Method for discretization of integral equations, structured matrices like Toeplitz and Cauchy, kernel and covariance matrices etc. In the LU factorization of sparse linear systems arising from the discretization of partial differential equations, the fill-in in the triangular factors often has low-rank structure. Hence, the sparse linear solve algorithms in STRUMPACK exploit the different dense rank-structured matrix formats to compress the fill-in. This leads to purely algebraic, fast and scalable (both with problem size and compute cores) approximate direct solvers or preconditioners. These preconditioners are mostly aimed at large sparse linear systems which result from the discretization of a partial differential equation, but are not limited to any particular type of problem. STRUMPACK also provides preconditioned GMRES and BiCGStab iterative solvers.
Apart from rank-structured compression, the STRUMPACK sparse solver also support compression of the factors using the ZFP library, a general purpose compression algorithm tuned for floating point data. This can be used with a specified precision, or with lossless compression.
The HODLR and Butterfly functionality in STRUMPACK is implemented through interfaces to the ButterflyPACK package: https://github.com/liuyangzhuan/ButterflyPACK
This software is owned by the U.S. Department of Energy. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, prepare derivative works, and perform publicly and display publicly. Beginning five (5) years after the date permission to assert copyright is obtained from the U.S. Department of Energy, and subject to any subsequent five (5) year renewals, the U.S. Government is granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, prepare derivative works, distribute copies to the public, perform publicly and display publicly, and to permit others to do so.
If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Technology Transfer Department at [email protected].