Scalable Duplicate Pruning Strategies for Parallel A* Graph Search

@inproceedings{Mahapatra1993ScalableDP,
  title={Scalable Duplicate Pruning Strategies for Parallel A* Graph Search},
  author={Nihar R. Mahapatra and Shantanu Dutt},
  booktitle={SPDP},
  year={1993}
}
In parallel A * graph search on distributed-memory machines, different processors may perform significant duplicated work if inter-processor duplicates are not pruned. The only known method for duplicate pruning associates a particular processor with each distinct node of the search space using a suitable hash function. Then duplicate nodes arising in different processors are transmitted to the same processor, and thereby pruned. There are two main drawbacks attributable to such an approach: (1… CONTINUE READING

Results and Topics from this paper.

Key Quantitative Results

  • Using the Traveling Salesman Problem (TSP) as a test case, we find that on a 10-dimensional nCUBE2 hypercube multicomputer, our pruning strategies yield a speedup improvement of more than 135% over previous methods that do not prune any duplicates, and more than 155% over the hashing-only pruning scheme.

References

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