{'fraction_non_alphanumeric': 0.039473684210526314, 'fraction_numerical': 0.019736842105263157, 'mean_word_length': 5.340277777777778, '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}}
Generalized matching from theory to application

We present a novel approach for post-mapping optimization. We exploit the concept of generalised matching, a technique that finds symbolically all possible matching assignments of library cells to a multi-output network specified by a Boolean relation. Several objectives are targeted: area minimization under delay constraints; power minimization under delay constraints; and unconstrained delay minimization. We describe the theory of generalized matching and the algorithmic optimization required for its efficient and robust implementation. A tool based on generalized matching has been implemented and tested on large examples of the MCNC'91 benchmark suite. We obtain sizable improvements in: speed (6% in average, up to 20.7%); area under speed constraints (13.7% an average, up to 29.5%); and power under speed constraints (22.3% in average, up to 38.1%).