Scalable DFA Compilation for High-Performance Regular-Expression Matching

Abstract

Regular-expression accelerators often rely on sophisticated compilers to fully exploit the available hardware capabilities for achieving wire-speed scan rates of multiple tens of gigabits per second. This paper presents a method for the efficient compilation of pattern-matching functions specified by deterministic finite automata (DFAs) into executable structures targeted at accelerators based on B-FSM programmable state machines. The compilation scheme presented is able to effectively exploit an adaptive compression mechanism to obtain one of the most compact state-transition-table structures in the industry, in combination with fast compilation times. The heuristic-based approach scales to very large DFAs having tens of millions of transitions, while achieving an approximately linear growth of the storage needs as a function of the DFA size.