TY - JOUR
T1 - Power Converter Circuit Design Automation Using Parallel Monte Carlo Tree Search
AU - Fan, Shaoze
AU - Zhang, Shun
AU - Liu, Jianbo
AU - Cao, Ningyuan
AU - Guo, Xiaoxiao
AU - Li, Jing
AU - Zhang, Xin
N1 - Funding Information:
The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award No. DE-AR0001210 and in part by the U.S. National Science Foundation, under Grant No. CNS-1948457. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
Publisher Copyright:
© 2022 Association for Computing Machinery.
PY - 2022/12/24
Y1 - 2022/12/24
N2 - The tidal waves of modern electronic/electrical devices have led to increasing demands for ubiquitous application-specific power converters. A conventional manual design procedure of such power converters is computation- and labor-intensive, which involves selecting and connecting component devices, tuning component-wise parameters and control schemes, and iteratively evaluating and optimizing the design. To automate and speed up this design process, we propose an automatic framework that designs custom power converters from design specifications using Monte Carlo Tree Search. Specifically, the framework embraces the upper-confidence-bound-tree (UCT), a variant of Monte Carlo Tree Search, to automate topology space exploration with circuit design specification-encoded reward signals. Moreover, our UCT-based approach can exploit small offline data via the specially designed default policy and can run in parallel to accelerate topology space exploration. Further, it utilizes a hybrid circuit evaluation strategy to substantially reduce design evaluation costs. Empirically, we demonstrated that our framework could generate energy-efficient circuit topologies for various target voltage conversion ratios. Compared to existing automatic topology optimization strategies, the proposed method is much more computationally efficient - the sequential version can generate topologies with the same quality while being up to 67% faster. The parallelization schemes can further achieve high speedups compared to the sequential version.
AB - The tidal waves of modern electronic/electrical devices have led to increasing demands for ubiquitous application-specific power converters. A conventional manual design procedure of such power converters is computation- and labor-intensive, which involves selecting and connecting component devices, tuning component-wise parameters and control schemes, and iteratively evaluating and optimizing the design. To automate and speed up this design process, we propose an automatic framework that designs custom power converters from design specifications using Monte Carlo Tree Search. Specifically, the framework embraces the upper-confidence-bound-tree (UCT), a variant of Monte Carlo Tree Search, to automate topology space exploration with circuit design specification-encoded reward signals. Moreover, our UCT-based approach can exploit small offline data via the specially designed default policy and can run in parallel to accelerate topology space exploration. Further, it utilizes a hybrid circuit evaluation strategy to substantially reduce design evaluation costs. Empirically, we demonstrated that our framework could generate energy-efficient circuit topologies for various target voltage conversion ratios. Compared to existing automatic topology optimization strategies, the proposed method is much more computationally efficient - the sequential version can generate topologies with the same quality while being up to 67% faster. The parallelization schemes can further achieve high speedups compared to the sequential version.
KW - Design automation
KW - Monte Carlo Tree Search (MCTS)
KW - circuit synthesis
KW - circuit topology design
KW - power converter
KW - upper-confidence-bound tree (UCT)
UR - http://www.scopus.com/inward/record.url?scp=85152478950&partnerID=8YFLogxK
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U2 - 10.1145/3549538
DO - 10.1145/3549538
M3 - Article
AN - SCOPUS:85152478950
SN - 1084-4309
VL - 28
JO - ACM Transactions on Design Automation of Electronic Systems
JF - ACM Transactions on Design Automation of Electronic Systems
IS - 2
M1 - 3549538
ER -