A number of techniques to improve the parsing performance of XML have been developed. Generally, however, these techniques have limited impact on the construction of a DOM tree, which can be a significant bottleneck. Meanwhile, the trend in hardware technology is toward an increasing number of cores per CPU. As we have shown in previous work, these cores can be used to parse XML in parallel, resulting in significant speedups. In this paper, we introduce a new static partitioning and load-balancing mechanism. By using a static, global approach, we reduce synchronization and load-balancing overhead, thus improving performance over dynamic schemes for a large class of XML documents. Our approach leverages libxml2 without modification, which reduces development effort and shows that our approach is applicable to real-world, production parsers. Our scheme works well with Sun’s Niagara class of CMT architectures, and shows that multiple hardware threads can be effectively used for XML parsing. 1.

A language for semi-structured documents, XML is playing crucial roles in web services, messaging systems, databases, and document processing. However, the processing of XML documents has been regarded as the performance bottleneck in most systems and applications. On the other side, the multicore processor, emerged as a solution for the clock-speed limitation of the modern CPUs, has been growingly prevalent. Leveraging the parallelism provided by the multicore resource to speedup the software execution is becoming the trend of the software development. In this paper, we present a parallel processing model for the XML document. The model is not designed just for a specific XML processing task, instead, it is a general model, by which we are able to explore various parallel XML document processing. The kernel of the model is a stealing-based dynamic load-balancing mechanism, by which multiple threads are able to process the disjointed parts of the XML document in parallel with balanced load distribution. The model also provides a novel mechanism to trace the stealing actions, thus the equivalent sequential result can be gotten by gluing the multiple parallel-running results together. To show the feasibility and effectiveness of our approaches, we present our C # implementation of parallel XML serialization in this paper. Our empirical study shows our parallel XML serialization algorithm can improved the XML serializing performance significantly on a multicore machine.