Ubuntu
amgcl package

amgcl 1.4.3-3 source package in Ubuntu

Changelog

amgcl (1.4.3-3) unstable; urgency=medium

  * Build-Depends: python3-dev, not python3-all-dev (Closes: #1024313)

 -- Dima Kogan <email address hidden>  Sat, 19 Nov 2022 14:47:54 -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

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File Size SHA-256 Checksum
amgcl_1.4.3-3.dsc 2.3 KiB 5a06c249e08138e1599a9f328b5dbf06f10585cfb43699fdf7eab29fcf2646dd
amgcl_1.4.3.orig.tar.gz 2.9 MiB e920d5767814ce697d707d1f359a16c9b9eb79eba28fe19e14c18c2a505fe0ad
amgcl_1.4.3-3.debian.tar.xz 5.2 KiB 91bf0827c5cee9746e4b99f967c63dc243d0997e0964d5f6b6a0c6ad536a79bd

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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