An efficient multicharacter transition string-matching engine based on the aho-corasick algorithm
ACM Transactions on Architecture and Code Optimization (TACO)
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Conventionally, dictionary-based string pattern matching (SPM) has been implemented as Aho-Corasick deterministic finite automaton (AC-DFA). Due to its large memory footprint, a large-dictionary AC-DFA can experience poor cache performance when matching against inputs with high match ratio on multicore processors. We propose a head-body finite automaton (HBFA), which implements SPM in two parts: a head DFA (H-DFA) and a body NFA (B-NFA). The H-DFA matches the dictionary up to a predefined prefix length in the same way as AC-DFA, but with a much smaller memory footprint. The B-NFA extends the matching to full dictionary lengths in a compact variable-stride branch data structure, accelerated by single-instruction multiple-data (SIMD) operations. A branch grafting mechanism is proposed to opportunistically advance the state of the H-DFA with the matching progress in the B-NFA. Compared with a fully populated AC-DFA, our HBFA prototype has $({