Ubuntu
amgcl package

amgcl 1.4.3-5 source package in Ubuntu

Changelog

amgcl (1.4.3-5) unstable; urgency=medium

  * Fixed build on 32-bit platforms. Again. (Closes: #1020834)

 -- Dima Kogan <email address hidden>  Mon, 02 Jan 2023 22:28:19 -0800

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Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Mantic release multiverse misc
Lunar release multiverse misc

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File Size SHA-256 Checksum
amgcl_1.4.3-5.dsc 2.3 KiB 390ae9e7dc350308489c44cdeb0e310bccb889ee3d956ae60bd2ca16bef2b30b
amgcl_1.4.3.orig.tar.gz 2.9 MiB e920d5767814ce697d707d1f359a16c9b9eb79eba28fe19e14c18c2a505fe0ad
amgcl_1.4.3-5.debian.tar.xz 6.1 KiB dc2d496b6fa65e6b184db3824bd101801594d72abbf6034e6d3f2b7e6a88f497

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Binary packages built by this source

libamgcl-dev: Solves large sparse linear systems with algebraic multigrid method

 AMG is one of the most effective iterative methods for solution of equation
 systems arising, for example, from discretizing PDEs on unstructured grids. The
 method can be used as a black-box solver for various computational problems,
 since it does not require any information about the underlying geometry. AMG is
 often used not as a standalone solver but as a preconditioner within an
 iterative solver (e.g. Conjugate Gradients, BiCGStab, or GMRES).
 .
 AMGCL builds the AMG hierarchy on a CPU and then transfers it to one of the
 provided backends. This allows for transparent acceleration of the solution
 phase with help of OpenCL, CUDA, or OpenMP technologies. Users may provide
 their own backends which enables tight integration between AMGCL and the user
 code.
 .
 AMG is a header-only C++ library, with the headers provided by this package.

python3-amgcl: Solves large sparse linear systems with algebraic multigrid method

 AMG is one of the most effective iterative methods for solution of equation
 systems arising, for example, from discretizing PDEs on unstructured grids. The
 method can be used as a black-box solver for various computational problems,
 since it does not require any information about the underlying geometry. AMG is
 often used not as a standalone solver but as a preconditioner within an
 iterative solver (e.g. Conjugate Gradients, BiCGStab, or GMRES).
 .
 AMGCL builds the AMG hierarchy on a CPU and then transfers it to one of the
 provided backends. This allows for transparent acceleration of the solution
 phase with help of OpenCL, CUDA, or OpenMP technologies. Users may provide
 their own backends which enables tight integration between AMGCL and the user
 code.
 .
 This package provides the Python interface