DeepCAT: A Cost-Efficient Online Configuration Auto-Tuning Approach for Big Data Frameworks-Reference-Cited by-同舟云学术

DeepCAT: A Cost-Efficient Online Configuration Auto-Tuning Approach for Big Data Frameworks

Published:2022-08-29 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 51st International Conference on Parallel Processing
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Author:

Dou Hui¹,Wang Yilun¹,Zhang Yiwen¹,Chen Pengfei²

Affiliation:

1. School of Computer Science and Technology, Anhui University, China

2. School of Computer Science and Engineering, Sun Yat-sen University, China

Funder

National Natural Science Foundation of China

Key-Area Research and Development Program of Guangdong Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3545008.3545018

Reference32 articles.

1. Omid Alipourfard , Hongqiang Harry Liu , Jianshu Chen , Shivaram Venkataraman , Minlan Yu , and Ming Zhang . 2017 . {CherryPick}: Adaptively Unearthing the Best Cloud Configurations for Big Data Analytics . In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17) . 469–482. Omid Alipourfard, Hongqiang Harry Liu, Jianshu Chen, Shivaram Venkataraman, Minlan Yu, and Ming Zhang. 2017. {CherryPick}: Adaptively Unearthing the Best Cloud Configurations for Big Data Analytics. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17). 469–482.

2. ACTGAN: Automatic Configuration Tuning for Software Systems with Generative Adversarial Networks

3. AutoConfig: automatic configuration tuning for distributed message systems

4. Configuring in-memory cluster computing using random forest

5. A Reinforcement Learning Approach to Online Web Systems Auto-configuration

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