Cart (Loading....) | Create Account
Close category search window
 

Parallel Processing of Large-Scale XML-Based Application Documents on Multi-core Architectures with PiXiMaL

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Head, M.R. ; Grid Comput. Res. Lab., SUNY Binghamton, Binghamton, NY, USA ; Govindaraju, M.

Very large scientific datasets are becoming increasingly available in XML formats. Our earlier benchmarking results show that parsing XML is a time consuming process when compared with binary formats optimized for largescale documents. This performance bottleneck will get exacerbated as size of XML data increases in e-science applications. Our focus in this paper is on addressing this performance bottleneck. In recent times, the microprocessor industry has made rapid strides towards chip multi processors (CMPs). The widely available XML parsers have been unable to take advantage of the opportunities presented by CMPs, instead, passing the task of parallelization to the application programmer. The paradigms used thus far to process large size XML documents on uniprocessors are not applicable for CMPs. We present the design, implementation, and performance analysis of PiXiMaL, a parallel processing library for large-scale XML-data files. In particular, we discuss an effective scheme to parallelize the tokenization process to achieve an overall performance increase when parsing large-scale XML documents that are increasingly in use today. Our approach is to build a DFA-based parser that recognizes a useful subset of the XML specification and converts the DFA into an NFA which can be applied on any subset of the input.

Published in:

eScience, 2008. eScience '08. IEEE Fourth International Conference on

Date of Conference:

7-12 Dec. 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.