Power Converter Circuit Design Automation Using Parallel Monte Carlo Tree Search

Document Type

Article

Publication Date

12-24-2022

Abstract

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.

Identifier

85152478950 (Scopus)

Publication Title

ACM Transactions on Design Automation of Electronic Systems

External Full Text Location

https://doi.org/10.1145/3549538

e-ISSN

15577309

ISSN

10844309

Issue

2

Volume

28

Grant

CNS-1948457

Fund Ref

National Science Foundation

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