TY - GEN
T1 - Accelerating Concurrency Control with Active Thread Adjustment
AU - Masumura, Kosei
AU - Hoshino, Takashi
AU - Kawashima, Hideyuki
N1 - Funding Information:
ACKNOWLEDGEMENT This work was supported by JSPS Kakenhi 19H04117, and the New Energy and Industrial Technology Development Organization (NEDO).
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - We attempted to improve the performance of Silo, a concurrency control protocol for inmemory DataBase Management System that performs well under high-contention work-loads. Adaptive backoff is known as an effective optimization method under high-contention workloads. As a result of analyzing, we found that its efficacy lies in the non-existence of conflict events rather than in the reduction of the conflict rate, which has been considered in the past. On the basis of this analysis, we propose a method of adjusting the number of active threads. We conducted experiments comparing Cicada, another concurrency control protocol, and our method applied to Silo. The results indicate that the proposed method enabled Silo to significantly outperform. We found that cache misses are related to the performance.
AB - We attempted to improve the performance of Silo, a concurrency control protocol for inmemory DataBase Management System that performs well under high-contention work-loads. Adaptive backoff is known as an effective optimization method under high-contention workloads. As a result of analyzing, we found that its efficacy lies in the non-existence of conflict events rather than in the reduction of the conflict rate, which has been considered in the past. On the basis of this analysis, we propose a method of adjusting the number of active threads. We conducted experiments comparing Cicada, another concurrency control protocol, and our method applied to Silo. The results indicate that the proposed method enabled Silo to significantly outperform. We found that cache misses are related to the performance.
KW - Concurrency control
KW - Conflict analysis
KW - Transaction processing
UR - http://www.scopus.com/inward/record.url?scp=85127556666&partnerID=8YFLogxK
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U2 - 10.1109/BigComp54360.2022.00060
DO - 10.1109/BigComp54360.2022.00060
M3 - Conference contribution
AN - SCOPUS:85127556666
T3 - Proceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022
SP - 280
EP - 287
BT - Proceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022
A2 - Unger, Herwig
A2 - Kim, Young-Kuk
A2 - Hwang, Eenjun
A2 - Cho, Sung-Bae
A2 - Pareigis, Stephan
A2 - Kyandoghere, Kyamakya
A2 - Ha, Young-Guk
A2 - Kim, Jinho
A2 - Morishima, Atsuyuki
A2 - Wagner, Christian
A2 - Kwon, Hyuk-Yoon
A2 - Moon, Yang-Sae
A2 - Leung, Carson
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022
Y2 - 17 January 2022 through 20 January 2022
ER -