Christian Schulz

  1. Advanced Coarsening Schemes for Graph Partitioning.

    Authors: Ilya Safro, Peter Sanders, Christian Schulz
    Subjects: Data Structures and Algorithms
    Abstract

    The graph partitioning problem is widely used and studied in many practical
    and theoretical applications. The multilevel strategies represent today one of
    the most effective and efficient generic frameworks for solving this problem on
    large-scale graphs. Most of the attention in designing the multilevel
    partitioning frameworks has been on the refinement phase. In this work we focus
    on the coarsening phase, which is responsible for creating structurally similar
    to the original but smaller graphs.

  2. Distributed Evolutionary Graph Partitioning.

    Authors: Peter Sanders, Christian Schulz
    Subjects: Neural and Evolutionary Computation
    Abstract

    We present a novel distributed evolutionary algorithm, KaFFPaE, to solve the
    Graph Partitioning Problem, which makes use of KaFFPa (Karlsruhe Fast Flow
    Partitioner). The use of our multilevel graph partitioner KaFFPa provides new
    effective crossover and mutation operators. By combining these with a scalable
    communication protocol we obtain a system that is able to improve the best
    known partitioning results for many inputs in a very short amount of time.

  3. Engineering a Scalable High Quality Graph Partitioner.

    Authors: Peter Sanders, Manuel Holtgrewe, Christian Schulz
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    We describe an approach to parallel graph partitioning that scales to
    hundreds of processors and produces a high solution quality. For example, for
    many instances from Walshaw's benchmark collection we improve the best known
    partitioning. We use the well known framework of multi-level graph
    partitioning.

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