High-performance regular expression scanning on the Cell/B.E. processor

Abstract

Matching regular expressions (regexps) is a very common work-load. For example, tokenization, which consists of recognizing words or keywords in a character stream, appears in every search engine indexer. Tokenization also consumes 30% or more of most XML processors' execution time and represents the first stage of any programming language compiler.Despite the multi-core revolution, regexp scanner generators like flex haven't changed much in 20 years, and they do not exploit the power of recent multi-core architectures (e.g., multiple threads and wide SIMD units). This is unfortunate, especially given the pervasive importance of search engines and the fast growth of our digital universe. Indexing such data volumes demands precisely the processing power that multi-cores are designed to offer.We present an algorithm and a set of techniques for using multi-core features such as multiple threads and SIMD instructions to perform parallel regexp-based tokenization.As a proof of concept, we present a family of optimized kernels that implement our algorithm, providing the features of flex on the Cell/B.E. processor at top performance. Our kernels achieve almost-ideal resource utilization (99.2% of the clock cycles are non-NOP issues). They deliver a peak throughput of 14.30 Gbps per Cell chip, and 9.76 Gbps on Wikipedia input: a remarkable performance, comparable to dedicated hardware solutions. Also, our kernels show speedups of 57-81× over flex on the Cell.Our approach is valuable because it is easily portable to other SIMD-enabled processors, and there is a general trend toward more and wider SIMD instructions in architecture design.