Power Converter Circuit Design Automation using Parallel Monte Carlo Tree Search
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- New Jersey Inst. of Technology, Newark, NJ (United States)
- IBM T. J. Watson Research Center, Cambridge, MA (United States)
- Univ. of Notre Dame, IN (United States)
- Meta Platforms Inc., Menlo Park, CA (United States)
- IBM T. J. Watson Research Center, Yorktown Heights, NY (United States)
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. Here, the parallelization schemes can further achieve high speedups compared to the sequential version.
- Research Organization:
- IBM, Cambridge, MA (United States)
- Sponsoring Organization:
- USDOE Advanced Research Projects Agency - Energy (ARPA-E); National Science Foundation (NSF)
- Grant/Contract Number:
- AR0001210; CNS–1948457
- OSTI ID:
- 1877055
- Journal Information:
- ACM Transactions on Design Automation of Electronic Systems, Vol. 28, Issue 2; ISSN 1084-4309
- Publisher:
- Association for Computing Machinery (ACM)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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