Boosting VLSI Design Flow Parameter Tuning with Random Embedding and Multi-objective Trust-region Bayesian Optimization
| العنوان: | Boosting VLSI Design Flow Parameter Tuning with Random Embedding and Multi-objective Trust-region Bayesian Optimization |
|---|---|
| المؤلفون: | Su Zheng, Hao Geng, Chen Bai, Bei Yu, Martin D.F. Wong |
| المصدر: | ACM Transactions on Design Automation of Electronic Systems. |
| بيانات النشر: | Association for Computing Machinery (ACM), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Electrical and Electronic Engineering, Computer Graphics and Computer-Aided Design, Computer Science Applications |
| الوصف: | Modern very large-scale integration (VLSI) design requires the implementation of integrated circuits using electronic design automation (EDA) tools. Due to the complexity of EDA algorithms, there are numerous tool parameters that have imperative impacts on the chip design quality. Manual selection of parameter values is excessively laborious and constrained by experts’ experience. Due to the high complexity and lack of parallelization, most existing parameter tuning methods cannot make sufficient exploration in a large search space. In this paper, we boost the efficiency and performance of parameter tuning with random embedding and multi-objective trust-region Bayesian optimization. Random embedding can effectively cut down the number of variables in the search process and thus reduce the runtime of Bayesian optimization. Multi-objective trust-region Bayesian optimization allows the algorithm to explore diverse solutions with excellent parallelism. Due to the ability to do more exploration in limited runtime, the proposed framework can achieve better performance than existing methods in our experiments. |
| تدمد: | 1557-7309 1084-4309 |
| DOI: | 10.1145/3597931 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::7c1ebbed43ca9a4a61efd8a5db41e595 https://doi.org/10.1145/3597931 |
| رقم الانضمام: | edsair.doi...........7c1ebbed43ca9a4a61efd8a5db41e595 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15577309 10844309 |
|---|---|
| DOI: | 10.1145/3597931 |