Demystifying automata processing
Marziyeh Nourian, Xiang Wang, Xiaodong Yu, Wu-chun Feng, Michela Becchi · 2017
Many established and emerging applications perform at their core some form of pattern matching, a computation that maps naturally onto finite automata abstractions. As a consequence, in recent years there has been a substantial amount of work on high-speed automata processing, which has led to a number of implementations targeting a variety of parallel platforms: CPUs, GPUs, FPGAs, ASICs, and Network Processors. More recently, Micron has announced its Automata Processor (AP), a DRAM-based accelerator of non-deterministic finite automata (NFA). Despite the abundance of work in this domain, the advantages and disadvantages of different automata processing accelerators and the innovation space in this area are still unclear.