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Fast block distributed CUDA implementation of the Hungarian algorithm
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DOI：10.1016/j.jpdc.2019.03.014.png)
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Abstract
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The Hungarian algorithm solves the linear assignment problem in polynomial time. A GPU/CUDA implementation of this algorithm is proposed. GPUs are massive parallel machines. In this implementation, the alternating path search phase of the algorithm is distributed by several blocks in a way to minimize global device synchronization. This phase is very important and has a big contribution to the execution time. Other advanced features also implemented are: parallel graph traversal; the parallel detection of multiple alternating paths in a single iteration; a simplified and fast matrix compression that stores the zeros of the slack matrix, resulting in very fast graph traversal; highly optimized reductions for the initial slack matrix calculation and update. This results in a fast implementation for moderate size problems. (C) 2019 Elsevier Inc. All rights reserved.
Keywords:
Hungarian algorithm
Linear assignment problem
GPU
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