Speculative p-DFAs for parallel XML parsing

XML has seen wide acceptance in a number of application domains, and contributed to the success of wide-scale grid and scientific computing environments. Performance, however, is still an issue, and limits adoption under some situations where it might otherwise be able to provide significant interoperability, flexibility, and extensibility. As CPUs increasingly have multiple cores, parallel XML parsing can help to address this concern. This paper explores the use of speculation to improve the performance of parallel XML parsing. Building on previous work, we use an initial preparsing stage to build a sketch of the document which we called the skeleton. This skeleton contains enough information so that we can then proceed to do the full parse in parallel using unmodified libxml2. The preparsing itself is parallelized using product machines which we call p-DFAs. During execution, unlikely possibilities are discarded in favor of more likely ones. Statistics are gathered to decide which possibilities are not likely. The results show good performance and scalability on both a 30 CPU Sun E6500 machine running Solaris and a Linux machine with two Intel Xeon L5320 CPUs for a total of 8 physical cores.