DocumentCode
1667795
Title
Matrix-Based XML Stream Processing Using a GPU
Author
Soo-Hyung Kim ; Yoon-Joon Lee ; Lee, John Jaehwan
Author_Institution
Sch. of Comput., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
fYear
2015
Firstpage
694
Lastpage
697
Abstract
With 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.
Keywords
Boolean functions; XML; graphics processing units; matrix algebra; parallel processing; query processing; GPGPU computing; XMark benchmark data set; XPath queries; bit-AND Boolean operations; massive parallel processing; matrix indexes; matrix-based XML stream processing; query processing; single-thread execution; Filtering; Graphics processing units; Indexes; Matrix converters; Matrix decomposition; Parallel processing; XML; GPGPU; Parallel Processing; XML Stream;
fLanguage
English
Publisher
ieee
Conference_Titel
Big Data (BigData Congress), 2015 IEEE International Congress on
Conference_Location
New York, NY
Print_ISBN
978-1-4673-7277-0
Type
conf
DOI
10.1109/BigDataCongress.2015.111
Filename
7207295
Link To Document