From: George Karypis Newsgroups: comp.parallel Subject: [ANNOUNCEMENT] ParMETIS 2.0: A Parallel Graph Partitioning and Sparse Date: 4 Oct 1998 03:40:11 GMT Organization: University of Minnesota, Twin Cities Campus Approved: bigrigg@cs.cmu.edu Message-Id: <6v6qmr$cl7$1@encore.ece.cmu.edu> Originator: bigrigg@ece.cmu.edu --Boundary_(ID_SlFgUMOOyH3m4LeSUZczbQ) Content-type: text/plain; charset=us-ascii Content-transfer-encoding: 7bit ParMETIS 2.0: A Parallel Graph Partitioning and Sparse Matrix Ordering Library ------------------------------------------------------------------------------ URL: http://www.cs.umn.edu/~metis URL: http://www.cs.umn.edu/~karypis/metis We would like to announce the release of version 2.0 of the ParMETIS library. ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs and for computing fill-reducing orderings for sparse matrices. ParMETIS is particularly suited for parallel numerical simulations involving large unstructured meshes. For these computations, ParMETIS dramatically reduces the time spent in communication by decomposing the mesh in a way that balances the load and minimizes the number of interface elements. ParMETIS's algorithms are based on the multilevel partitioning and fill reducing ordering algorithms that are implemented in the widely used serial package METIS. ParMETIS extends the functionality provided by METIS by including routines that are especially suited for parallel computations and large scale numerical simulations. ParMETIS provides the following four major functions: - Partition an unstructured graph. - Improve the quality of an existing partition. - Repartition a graph that corresponds to an adaptively refined mesh. - Compute a fill-reducing ordering for sparse direct factorization. Here is a list of the major changes in version 2.0 - Improved support for repartitioning graphs corresponding to adaptively refined meshes. * Two new adaptive repartitioning routines have been added that are based on the remapping paradigm. * The directed diffusion algorithm has been improved and uses a newly developed wavefront formulation. - The number of partitions have been de-coupled from the number of processors. you can now use the parallel partitioning algorithms to compute a k-way partitioning independent of the number of processors that are used. This is particularly useful for parallel computers consisting of clusters of SMPs. - The names and calling sequences of all the routines have changed to make it easier to call the various routines from Fortran. - The partitioning and ordering algorithms in ParMETIS now utilize various portions of the serial METIS library. As a result, the quality of the partitionings and orderings have been improved. Obtaining ParMETIS ------------------ ParMETIS is distributed freely. Information on how to download the source code is available on WWW at URL: http://www.cs.umn.edu/~metis or URL: http://www.cs.umn.edu/~karypis/metis ParMETIS has been written by George Karypis, at the Computer Science Department of the University of Minnesota. If you have any questions or problems obtaining ParMETIS, send email to metis@cs.umn.edu. --Boundary_(ID_SlFgUMOOyH3m4LeSUZczbQ) Content-type: text/html; charset=us-ascii Content-transfer-encoding: 7bit
ParMETIS 2.0: A Parallel Graph Partitioning and Sparse Matrix Ordering Library
------------------------------------------------------------------------------

URL: http://www.cs.umn.edu/~metis
URL: http://www.cs.umn.edu/~karypis/metis

We would like to announce the release of version 2.0 of the ParMETIS library.
ParMETIS is an MPI-based parallel library that implements a variety of
algorithms for partitioning unstructured graphs and for computing
fill-reducing orderings for sparse matrices. ParMETIS is particularly suited
for parallel numerical simulations involving large unstructured meshes.
For these computations, ParMETIS dramatically reduces the time spent in
communication by decomposing the mesh in a way that balances the load and
minimizes the number of interface elements.

ParMETIS's algorithms are based on the multilevel partitioning and fill
reducing ordering algorithms that are implemented in the widely used serial
package METIS. ParMETIS extends the functionality provided by METIS by
including routines that are especially suited for parallel computations and
large scale numerical simulations.

ParMETIS provides the following four major functions:
- Partition an unstructured graph.
- Improve the quality of an existing partition.
- Repartition a graph that corresponds to an adaptively refined mesh.
- Compute a fill-reducing ordering for sparse direct factorization.

Here is a list of the major changes in version 2.0
- Improved support for repartitioning graphs corresponding to adaptively
    refined meshes.
    * Two new adaptive repartitioning routines have been added that are based
      on the remapping paradigm.
    * The directed diffusion algorithm has been improved and uses a newly
      developed wavefront formulation.
- The number of partitions have been de-coupled from the number of processors.
    you can now use the parallel partitioning algorithms to compute a k-way
    partitioning independent of the number of processors that are used. This
    is particularly useful for parallel computers consisting of clusters of
    SMPs.
- The names and calling sequences of all the routines have changed to make it
    easier to call the various routines from Fortran.
- The partitioning and ordering algorithms in ParMETIS now utilize various
    portions of the serial METIS library. As a result, the quality of the
    partitionings and orderings have been improved.

Obtaining ParMETIS
------------------

ParMETIS is distributed freely. Information on how to download the source
code is available on WWW at

URL: http://www.cs.umn.edu/~metis
or
URL: http://www.cs.umn.edu/~karypis/metis

ParMETIS has been written by George Karypis, at the Computer Science
Department of the University of Minnesota. If you have any questions or
problems obtaining ParMETIS, send email to metis@cs.umn.edu.

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