- Published 2012 in J. Parallel Distrib. Comput.

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 tradeoff.

@article{Saule2012LoadBalancingSL,
title={Load-Balancing Spatially Located Computations using Rectangular Partitions},
author={Erik Saule and Erdeniz {\"{O}. Bas and {\"{U}mit V. Çataly{\"{u}rek},
journal={J. Parallel Distrib. Comput.},
year={2012},
volume={72},
pages={1201-1214}
}