executing parallel twigstack algorithm on a multi-core system
The advancement of multi-core processors technology has led to changing course of computing and enabled us to maximize the computing performance. In this study, we present a parallel TwigStack algorithm executed on a shared-memory multi-core system for achieving scalable query performance against large XML data. Our proposed scheme explores the following features. Firstly, we perform on-the-fly partitioning on input streams of XML nodes for subsequent parallel execution and, thereby, ensure that query solutions in a partition can be obtained by the TwigStack algorithm without being dependent on other partitions. Secondly, we propose a scheme for estimating the optimal partition size for a given system configuration by taking L2-cache size into account. Finally, we introduce a partition prefetching technique to alleviate the overheads of performing the on-the-fly partitions. The experimental results demonstrate that our proposed parallel algorithm works effectively and efficiently. The parallel speedup scales up to the number of available CPU-cores.
parallel twigstack multi-core system xml data partition