Evaluations of Hash Distributed A* in Optimal Sequence Alignment
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 584-589.
Abstract
Hash Distributed A* (HDA*) is a parallel A* algorithm that is proven to be effective in optimal sequential planning with unit edge costs. HDA* leverages the Zobrist function to almost uniformly distribute and schedule work among processors. This paper evaluates the performance of HDA* in optimal sequence alignment. We observe that with a large number of CPU cores HDA* suffers from an increase of search overhead caused by reexpansions of states in the closed list due to nonuniform edge costs in this domain. We therefore present a new work distribution strategy limiting processors to distribute work, thus increasing the possibility of detecting such duplicate search effort. We evaluate the performance of this approach on a cluster of multi-core machines and show that the approach scales well up to 384 CPU cores.
@inproceedings{ijcai2011p105,
title = {Evaluations of Hash Distributed A* in Optimal Sequence Alignment},
author = {Kobayashi, Yoshikazu and Kishimoto, Akihiro and Watanabe, Osamu},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {584--589},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-105},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-105},
}
TY - CPAPER TI - Evaluations of Hash Distributed A* in Optimal Sequence Alignment AU - Kobayashi, Yoshikazu AU - Kishimoto, Akihiro AU - Watanabe, Osamu T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 584 EP - 589 DO - 10.5591/978-1-57735-516-8/IJCAI11-105 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-105 ER -Copied
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