Reinforcement Learning-based Optimal On-board Decoupling Capacitor Design Method

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In this paper, for the first time, we propose a reinforcement learning-based optimal on-board decoupling capacitor (decap) design method. The proposed method can provide optimal decap designs for a given on-board power distribution network (PDN). An optimal decap design refers to the optimized combination of decaps at proper positions to satisfy a required target impedance. Moreover, a minimum number of decaps should be assigned for optimal decap designs. The proposed method is applied to the test on-board PDN and successfully provided 37 optimal decap designs with 4 decaps assigned each. Self impedance of PDN with the provided design satisfied the required target impedance while minimizing the number of assigned decaps.
Publisher
IEEE
Issue Date
2018-10-15
Language
English
Citation

27th IEEE Conference on Electrical Performance on Electronic Packaging and Systems (EPEPS), pp.213 - 215

DOI
10.1109/EPEPS.2018.8534195
URI
http://hdl.handle.net/10203/248872
Appears in Collection
EE-Conference Papers(학술회의논문)
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