Evaluations of Hash Distributed A* in Optimal Sequence Alignment
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.
Cite
Text
Kobayashi et al. "Evaluations of Hash Distributed A* in Optimal Sequence Alignment." International Joint Conference on Artificial Intelligence, 2011. doi:10.5591/978-1-57735-516-8/IJCAI11-105Markdown
[Kobayashi et al. "Evaluations of Hash Distributed A* in Optimal Sequence Alignment." International Joint Conference on Artificial Intelligence, 2011.](https://mlanthology.org/ijcai/2011/kobayashi2011ijcai-evaluations/) doi:10.5591/978-1-57735-516-8/IJCAI11-105BibTeX
@inproceedings{kobayashi2011ijcai-evaluations,
title = {{Evaluations of Hash Distributed A* in Optimal Sequence Alignment}},
author = {Kobayashi, Yoshikazu and Kishimoto, Akihiro and Watanabe, Osamu},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2011},
pages = {584-590},
doi = {10.5591/978-1-57735-516-8/IJCAI11-105},
url = {https://mlanthology.org/ijcai/2011/kobayashi2011ijcai-evaluations/}
}