AMGCL: an Efficient, Flexible, and Extensible Algebraic Multigrid Implementation

Abstract

The paper presents AMGCL -- an opensource C++ library implementing the algebraic multigrid method (AMG) for solution of large sparse linear systems of equations, usually arising from discretization of partial differential equations on an unstructured grid. The library supports both shared and distributed memory computation, allows to utilize modern massively parallel processors via OpenMP, OpenCL, or CUDA technologies, has minimal dependencies, and is easily extensible. The design principles behind AMGCL are discussed and it is shown that the code performance is on par with alternative implementations.

Cited by in corpus (9)

• Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence
• Accelerating linear solvers for Stokes problems with C++ metaprogramming
• PyMatting: A Python Library for Alpha Matting
• A Hybrid Lagrangian/Eulerian Collocated Advection and Projection Method for Fluid Simulation
• MPMNet: A Data-Driven MPM Framework for Dynamic Fluid-Solid Interaction
• Barrier-Augmented Lagrangian for GPU-based Elastodynamic Contact
• Subdomain Deflation Combined with Local AMG: a Case Study Using AMGCL Library
• Large-scale semi-discrete optimal transport with distributed Voronoi diagrams
• JAX-AMG: A GPU-Accelerated Differentiable Sparse Linear Solver Library for JAX