<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
<pkgmetadata>
	<herd>sci</herd>
	<longdescription lang="en">AMG is a multilevel technique for solving large-scale linear systems
  with optimal or near-optimal efficiency. Unlike geometric multigrid,
  AMG requires little or no geometric information about the underlying
  problem and develops a sequence of coarser grids directly from the
  input matrix. This feature is especially important for problems
  discretized on unstructured meshes and irregular grids.
  PyAMG features implementations of: 
  * Ruge-Stuben (RS) or Classical AMG
  * AMG based on Smoothed Aggregation (SA)
  and experimental support for:
  * Adaptive Smoothed Aggregation (αSA)
  * Compatible Relaxation (CR)
  The predominant portion of PyAMG is written in Python with a smaller
  amount of supporting C++ code for performance critical operations.</longdescription>
	<upstream>
		<remote-id type="google-code">pyamg</remote-id>
	</upstream>
</pkgmetadata>