Job-Level Computing With BOINC Support
| dc.citation.epage | 206 | en_US |
| dc.citation.spage | 200 | en_US |
| dc.contributor.author | Chang, Chia-Chuan | en_US |
| dc.contributor.author | Wei, Ting-Han | en_US |
| dc.contributor.author | Wu, I-Chen | en_US |
| dc.contributor.department | 資訊工程學系 | zh_TW |
| dc.contributor.department | Department of Computer Science | en_US |
| dc.date.accessioned | 2018-08-21T05:56:50Z | |
| dc.date.available | 2018-08-21T05:56:50Z | |
| dc.date.issued | 2016-01-01 | en_US |
| dc.description.abstract | Recently, Wu et al. introduced a general approach based on distributed computing named Job-Level (JL) Computing. JL Computing has been successfully used to construct the opening books of game-playing programs. In order to support large-scale computing problems such as solving 7x7 killall-Go, or building opening books for 9x9 Go or Connect6, record databases are used to store JL computing results. In this paper, we further design a mechanism that combines the JL computing system with BOINC (Berkeley Open Infrastructure for Network Computing), so that we can leverage more computing power from volunteers to solve even larger problems. A preliminary experiment has been done to demonstrate the feasibility of the design. | en_US |
| dc.identifier.issn | 2376-6816 | en_US |
| dc.identifier.journal | 2016 CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI) | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/146720 | |
| dc.identifier.wosnumber | WOS:000406594200027 | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Job-Level computing | en_US |
| dc.subject | volunteer computing | en_US |
| dc.subject | BOINC | en_US |
| dc.subject | killall-Go | en_US |
| dc.title | Job-Level Computing With BOINC Support | en_US |
| dc.type | Proceedings Paper | en_US |
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