Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search

Authors

  • Yuu Jinnai The University of Tokyo
  • Alex Fukunaga The University of Tokyo

DOI:

https://doi.org/10.1609/aaai.v30i1.10065

Keywords:

Heuristic Search, Parallel Search, Work Distribution

Abstract

Hash Distributed A* (HDA*) is an efficient parallel best first algorithm that asynchronously distributes work among the processes using a global hash function. Although Zobrist hashing, the standard hash function used by HDA*, achieves good load balance for many domains, it incurs significant communication overhead since it requires many node transfers among threads. We propose Abstract Zobrist hashing, a new work distribution method for parallel search which reduces node transfers and mitigates communication overhead by using feature projection functions. We evaluate Abstract Zobrist hashing for multicore HDA*, and show that it significantly outperforms previous work distribution methods.

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Published

2016-02-21

How to Cite

Jinnai, Y., & Fukunaga, A. (2016). Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.10065

Issue

Section

Technical Papers: Heuristic Search and Optimization