Can I read Performance Enhancement with Speculative Execution Based Parallelism for Processing Large-scale Xml-based Application Data on EtoBox?

Performance Enhancement with Speculative Execution Based Parallelism for Processing Large-scale Xml-based Application Data by Michael R. Head; Madhusudhan Govindaraju is a scholarly article available to read on EtoBox.

What is Performance Enhancement with Speculative Execution Based Parallelism for Processing Large-scale Xml-based Application Data about?

We present the design and implementation of a toolkit for processing large-scale XML datasets that utilizes the capabilities for parallelism that are available in the emerging multi-core architectures. Multi-core processors are expected to be widely available in research clusters and scientific desktops, and it is critical to harness the opportunities for parallelism in the middleware, instead of passing on the task to application programmers. An emerging trend is the use of XML as the data format for many distributed/grid applications, with the size of these documents ranging from tens of megabytes to hundreds of megabytes. Our earlier benchmarking results revealed that most of the widely available XML processing toolkits do not scale well for large sized XML data. A significant transformation is necessary in the design of XML processing for distributed applications so that the overall application turn-around time is not negatively affected by XML processing. We discuss XML processing using PiXiMaL, a parallel processing library for large-scale XML datasets. The parallelization approach is to build a DFA-based parser that recognizes a useful subset of the XML specification, and co

Author

Michael R. Head; Madhusudhan Govindaraju

Publisher

ACM

Published

2009

Language

EN