{'fraction_non_alphanumeric': 0.03134110787172012, 'fraction_numerical': 0.0, 'mean_word_length': 5.476415094339623, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A New SQP Based Space-Mapping Algorithm for On-Chip Spiral Inductor Optimization

Computer aided design (CAD) and optimization of on-chip spiral inductors is of immense interest to RFIC designers. Traditional optimization methods rely on approximate/fast "coarse models" of spiral inductors, e.g. equivalent circuits, empirical equations, etc. Naturally, the accuracy/validity of optimized results from such methods depends highly on the quality of the coarse models used. Further, the inability of such models to account for full-wave electromagnetic (EM) effects, limits their application to low-frequency circuit designs and/or necessitates additional efforts to formulate an acceptable optimization objective. The pressing need for first-pass success of CAD tools in terms of inductor design mandates consideration of full-wave EM effects within the CAD framework. Space-mapping optimization combines the speed of circuit models and the accuracy of EM simulations. In this paper, we propose a new space-mapping optimization algorithm, which exploits the sequential quadratic programming (SQP) technique for coarse model optimization. Starting with the user-specifications of the spiral inductor, the proposed algorithm yields an acceptable spiral inductor design/layout for RFIC design. The algorithm is illustrated via an on-chip spiral inductor optimization example.