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Parallel Graph Partitioning and Fill-reducing Matrix Ordering
developed in Karypis Lab at the University of Minnesota

ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs, meshes, and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning, adaptive repartitioning, and parallel multi-constrained partitioning schemes developed in Karypis Lab.
ParMETIS provides the following five major functions:

  • Graph Partitioning
  • Mesh Partitioning
  • Graph Repartitioning
  • Partitioning Refinement
  • Matrix Reordering