[SciPy-user] ANN: PyAMG v1.0 (Algebraic Multigrid Solvers in Python)

Nathan Bell wnbell@gmail....
Thu Mar 5 13:26:49 CST 2009

We are pleased to announce the first release of PyAMG: Algebraic
Multigrid Solvers in Python.  With a user-friendly interface and
efficient implementation, PyAMG addresses the growing demand for
scalable solvers by non-experts. PyAMG features implementations of
    * Ruge-Stuben (RS) or Classical AMG
    * AMG based on Smoothed Aggregation (SA)
and experimental support for
    * Adaptive Smoothed Aggregation (=E1SA)
    * Compatible Relaxation (CR)
along with many tunable options for coarsening, interpolation,
relaxation, prolongator smoothing.

Our goal with the PyAMG project is to provide a framework for existing
AMG methods and to allow for quick testing and prototyping of
additional functionality and algorithms.  Specifically, our objectives
   * ease of use
         o interface is accessible to non-experts
         o extensive documentation and references
   * speed
         o solves problems with millions of unknowns efficiently
         o core multigrid algorithms are implemented in C++
         o sparse matrix support is provided by scipy.sparse
   * readability
         o source code is organized into intuitive components
   * extensibility
         o core components can be reused to implement additional techniques
         o new features are easy integrated
   * experimentation
         o facilitates rapid prototyping and analysis of multigrid methods
   * portability
         o tested on several platforms (Linux, Windows, Mac)
         o relies only on Python, NumPy, and SciPy

PyAMG relies extensively on the NumPy and SciPy libraries for
scientific programming with Python.  We thank the NumPy/SciPy
community for their support and continued efforts.

For more information see

PyAMG developers:
       Nathan Bell (http://graphics.cs.uiuc.edu/~wnbell/)
       Luke Olson (http://www.cs.uiuc.edu/homes/lukeo/)
       Jacob Schroder (www.cse.uiuc.edu/~jschrod3/)

Nathan Bell wnbell@gmail.com

More information about the SciPy-user mailing list