Design of a language-independent parallel string matching unit for NLP

In natural language processing applications, string matching is the main time-consuming operation due to the large size of lexicon. Data dependence is minimal in string matching operations, and hence it is ideal for parallelization. A dedicated hardware for string matching that uses memory interleaving and parallel processing techniques can relieve the host CPU from this burden, thereby making the system suitable for real-time applications. This paper reports the FPGA design of such a system with m parallel matching units. The time complexity of the proposed algorithm is O (log₂ n), where n is the total number of lexical entries. This has been achieved by a proper selection of the value of m. A special memory organization technique, which reduces the storage space by nearly 70%, has been adopted for storing lexical entries. The techniques used for matching and storage of lexical entries make the system language independent