NDLI: Approaching a parallelized XML parser optimized for multi-coreprocessors

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Approaching a parallelized XML parser optimized for multi-coreprocessors

Content Provider	ACM Digital Library
Author	Govindaraju, Madhusudhan Head, Michael R.
Abstract	Very large scientific datasets are increasingly becoming available in XML formats. At the same time, multi-core processing is increasingly becoming available on desktop- and laptop-class computing machines. Unfortunately, most XML parsers are still using algorithms that are inherently serial, which show little improvement on newer computing hardware. The current XML implementation landscape does not adequately meet the performance requirements of large scale applications. Thus far, applications using Web services (in the grid community, for example) have largely focused on XML protocol standardization and tool building efforts, and not on addressing the performance bottlenecks when dealing with large volumes of XML data. Generic parallel parsing has been studied in depth over the past thirty years. However, as yet, these results have not been applied to the problem of XML parsing. XML documents have some structural properties that make it more amenable to parallelized parsing than general context-free languages. As has been previously shown, XML parsers spend a large percentage of time tokenizing the input in aninherently serial process, typically running a deterministic finite automaton on the input. Our initial approach, described here, separates the process of parsing the XML from the process of reading the input. We take a well-known high performance parser, Piccolo, and apply two different strategies, Runahead and Piped, and examine the timing of the file read time and hence the overall time to parse large scientific XML files. Under the conditions tested here, performance decreases.
Starting Page	17
Ending Page	22
Page Count	6
File Format	PDF
ISBN	9781595937179
DOI	10.1145/1272457.1272460
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-06-25
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Parsing Xml Multi-core Parallelization
Content Type	Text
Resource Type	Article

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