Chaco contains a wide variety of algorithms and options, many of which were
invented by the authors. Some of the algorithms exploit the geometry of the
mesh, others its local connectivity or its global structure as captured by
eigenvectors of a related matrix. These methods can be mixed and matched in
several ways, and combinations often prove to be more effective than any single
technique in isolation. All these algorithms are accessed via a simple user
interface, or a call from other software. Innovations in Chaco include

 * Development of multilevel graph partitioning. This widely imitated approach
 has become the premiere algorithm combining very high quality with short
 calculation times.

 * Extension of spectral partitioning to enable the use of 2 or 3 Laplacian
 eigenvectors to quadrisect of octasect a graph.

 * Highly efficient and robust eigensolvers for use with spectral graph
 algorithms.

 * Generalization of the Kernighan-Lin/Fiduccia-Mattheyses algorithm to handle
 weighted graphs, arbitrary number of sets and lazy initiation.

 * Development of skewed partitioning to improve the mapping of a graph onto a
 target parallel architecture.

 * Various post-processing options to improve partitions in a number of ways.

• Eugeny A. Rostovtsev (REAL)

• chaco
• chaco-docs
• libchaco
• libchaco-devel
• libchaco-devel-static