Matrix-based XML Stream Processing Using a GPU

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dc.contributor.authorKim, Soo Hyungko
dc.contributor.authorLee, John Jaehwanko
dc.contributor.authorLee, Yoon-Joonko
dc.date.accessioned2015-07-22T02:48:54Z-
dc.date.available2015-07-22T02:48:54Z-
dc.date.created2015-07-06-
dc.date.created2015-07-06-
dc.date.created2015-07-06-
dc.date.issued2015-06-27-
dc.identifier.citation2015 IEEE International Congress on Big Data, pp.694 - 697-
dc.identifier.urihttp://hdl.handle.net/10203/199828-
dc.description.abstractWith the advent of GPGPU computing, a major paradigm shift in parallel computation in recent years, massive parallel processing, has become available at a relatively low cost. However, conventional XML stream processing algorithms do not utilize the advantages of GPUs since the algorithms were intended for single-thread execution. In this research, we propose a GPU-accelerated, matrix-based XML stream processing methodology in which a large collection of XPath queries are transformed into matrixes of binary values and the XML stream is also converted to two matrix indexes. Then, the processing of a number of queries is transformed to simple bit-AND Boolean operations. With the XMark benchmark data set, we show that the proposed algorithm outperforms the conventional algorithms by about eight times.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleMatrix-based XML Stream Processing Using a GPU-
dc.typeConference-
dc.identifier.wosid000380443700101-
dc.identifier.scopusid2-s2.0-84959465330-
dc.type.rimsCONF-
dc.citation.beginningpage694-
dc.citation.endingpage697-
dc.citation.publicationname2015 IEEE International Congress on Big Data-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationMillennium Broadway Hotel, New York-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorLee, Yoon-Joon-
dc.contributor.nonIdAuthorLee, John Jaehwan-
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