2024-03-29T19:35:02Zhttps://ipsj.ixsq.nii.ac.jp/ej/?action=repository_oaipmhoai:ipsj.ixsq.nii.ac.jp:000870662022-10-21T05:24:51Z00581:06644:06923
Two-level Task Scheduling for Parallel Game Tree Search Based on NecessityTwo-level Task Scheduling for Parallel Game Tree Search Based on Necessityeng[特集:ゲームプログラミング] game tree search, distributed computing, scheduling algorithm, speculative executionhttp://id.nii.ac.jp/1001/00087051/Journal Articlehttps://ipsj.ixsq.nii.ac.jp/ej/?action=repository_action_common_download&item_id=87066&item_no=1&attribute_id=1&file_no=1Copyright (c) 2012 by the Information Processing Society of JapanGraduate School of Engineering, The University of TokyoInstitute of Industrial Science, The University of TokyoGraduate School of Engineering, The University of TokyoAkira, UraDaisaku, YokoyamaTakashi, ChikayamaIt is difficult to fully utilize the parallelism of large-scale computing environments in alpha-beta search. The naive parallel execution of subtrees would result in much less task pruning than may have been possible in sequential execution. This may even degrade total performance. To overcome this difficulty, we propose a two-level task scheduling policy in which all tasks are classified into two priority levels based on the necessity for their results. Low priority level tasks are only executed after all high priority level tasks currently executable have started. When new high priority level tasks are generated, the execution of low priority level tasks is suspended so that high level tasks can be executed. We suggest tasks be classified into the two levels based on the Young Brothers Wait Concept, which is widely used in parallel alpha-beta search. The experimental results revealed that the scheduling policy suppresses the degradation in performance caused by executing tasks whose results are eventually found to be unnecessary. We found the new policy improved performance when task granularity was sufficiently large.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.21(2013) No.1 (online)DOI http://dx.doi.org/10.2197/ipsjjip.21.17------------------------------It is difficult to fully utilize the parallelism of large-scale computing environments in alpha-beta search. The naive parallel execution of subtrees would result in much less task pruning than may have been possible in sequential execution. This may even degrade total performance. To overcome this difficulty, we propose a two-level task scheduling policy in which all tasks are classified into two priority levels based on the necessity for their results. Low priority level tasks are only executed after all high priority level tasks currently executable have started. When new high priority level tasks are generated, the execution of low priority level tasks is suspended so that high level tasks can be executed. We suggest tasks be classified into the two levels based on the Young Brothers Wait Concept, which is widely used in parallel alpha-beta search. The experimental results revealed that the scheduling policy suppresses the degradation in performance caused by executing tasks whose results are eventually found to be unnecessary. We found the new policy improved performance when task granularity was sufficiently large.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.21(2013) No.1 (online)DOI http://dx.doi.org/10.2197/ipsjjip.21.17------------------------------AN00116647情報処理学会論文誌53112012-11-151882-77642012-11-12