Accelerating XML Query Matching through Custom Stack Generation on FPGAs

Publish-subscribe systems present the state of the art in information dissemination to multiple users. Such systems have evolved from simple topic-based to the current XML-enabled systems. Here, users pose complex queries (expressed in XPath) on the structure and content of the streaming documents. The parts of the documents that match the user queries are then returned to the users. This paper proposes a novel hardware architecture that would exploit the parallelism found in XPath filtering systems. Using an incoming XML stream, parsing and matching with thousands of user profiles are performed simultaneously on a single FPGA, thus yielding up to three orders of magnitude higher throughput when compared to conventional approaches bound by the sequential aspect of software computing. By converting XPath expressions into custom stacks, our architecture is the first providing full support for all structural XPath constructs, including parent-child and ancestor descendant relations, whilst allowing wildcarding and recursion.