Load-balancing spatially located computations using rectangular partitions

  • Authors:

  • Erik Saule;Erdeniz Ö. Baş;íMit V. ÇAtalyüRek

  • Affiliations:

  • Department of Biomedical Informatics, The Ohio State University, OH 43212, Columbus, United States;Department of Biomedical Informatics, The Ohio State University, OH 43212, Columbus, United States and Department of Computer Science and Engineering, The Ohio State University, OH 43212, Columbus ...;Department of Biomedical Informatics, The Ohio State University, OH 43212, Columbus, United States and Department of Electrical and Computer Engineering, The Ohio State University, OH 43212, Colum ...

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2012

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Abstract

Distributing spatially located heterogeneous workloads is an important problem in parallel scientific computing. We investigate the problem of partitioning such workloads (represented as a matrix of non-negative integers) into rectangles, such that the load of the most loaded rectangle (processor) is minimized. Since finding the optimal arbitrary rectangle-based partition is an NP-hard problem, we investigate particular classes of solutions: rectilinear, jagged and hierarchical. We present a new class of solutions called m-way jagged partitions, propose new optimal algorithms for m-way jagged partitions and hierarchical partitions, propose new heuristic algorithms, and provide worst case performance analyses for some existing and new heuristics. Moreover, the algorithms are tested in simulation on a wide set of instances. Results show that two of the algorithms we introduce lead to a much better load balance than the state-of-the-art algorithms. We also show how to design a two-phase algorithm that reaches different time/quality tradeoffs.