Database Caching for Job-Level Computing

• Main Authors: Chiang, Han, 江翰
• Other Authors: Wu, I-Chen
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/38bx46

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 105 === This thesis improves upon Job-Level (JL) computing, a general distributed computing approach. In JL computing, a client maintains the overall search tree and encapsulates the overall search into coarse-grained jobs, which are then each calculated by pre-existing game-playing programs. In order to support large-scale problems such as solving 7x7 killall-Go, or building opening books for 9x9 Go or Connect6, JL computing is modified so that the entire search tree is stored in a database, as opposed to simply being stored in the client process’ memory. However, the time cost of accessing this database becomes a bottleneck on performance when using a large number of computing resources. This thesis proposes a cache mechanism for JL search trees. Instead of the previous approach, where the entire search tree is stored in the database, we maintain parts of the search tree in the memory of the client process to reduce the number of database accesses. Our method significantly improves the performance of job operations. We can perform 8.96 jobs/second on average without using the cache mechanism (not taking into consideration the job execution time). With the cache mechanism, the same application can perform up to 167.88 jobs/second. The data access speed is 18 times faster of the original approach when using the cache mechanism.