Transfer learning for Bayesian optimization: A survey
A wide spectrum of design and decision problems, including parameter tuning, A/B testing
and drug design, intrinsically are instances of black-box optimization. Bayesian optimization …
and drug design, intrinsically are instances of black-box optimization. Bayesian optimization …
KeenTune: Automated tuning tool for cloud application performance testing and optimization
Q Wang, R Wang, Y Hu, X Shi, Z Liu, T Ma… - Proceedings of the …, 2023 - dl.acm.org
The performance testing and optimization of cloud applications is challenging, because
manual tuning of cloud computing stacks is tedious and automated tuning tools are rare …
manual tuning of cloud computing stacks is tedious and automated tuning tools are rare …
KnobCF: Uncertainty-aware Knob Tuning
Y Yan, J Huang, H Wang, J Geng, K Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
The knob tuning aims to optimize database performance by searching for the most effective
knob configuration under a certain workload. Existing works suffer two significant problems …
knob configuration under a certain workload. Existing works suffer two significant problems …
INTOP: Improving Nginx Performance by Tuning OS Parameters
W Chen, L Li, Z Yu - … Conference on High Performance Big Data …, 2023 - ieeexplore.ieee.org
The performance of web servers is extremely important to the user experience of internet
users. However, we find that the performance of Nginx, the most popular web server, under …
users. However, we find that the performance of Nginx, the most popular web server, under …
Pushing the boundary: Specialising deep configuration performance learning
J Gong - 2024 - repository.lboro.ac.uk
Software systems often come with a multitude of configuration options that can be adjusted
to adapt their performance (eg, latency, execution time, and energy consumption) to various …
to adapt their performance (eg, latency, execution time, and energy consumption) to various …