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A hardware compilation framework for text analytics queries.

Authors :
Polig, Raphael
Atasu, Kubilay
Giefers, Heiner
Hagleitner, Christoph
Chiticariu, Laura
Reiss, Frederick
Zhu, Huaiyu
Hofstee, Peter
Source :
Journal of Parallel & Distributed Computing. Jan2018, Vol. 111, p260-272. 13p.
Publication Year :
2018

Abstract

Unstructured text data is being generated at an unprecedented rate in the form of Twitter feeds, machine logs or medical records. The analysis of this data is an important step to gaining significant insight regarding innovation, security and decision-making. The performance of traditional compute systems struggles to keep up with the rapid data growth and the expected high quality of information extraction. To cope with this situation, a compilation framework is presented that can transform text analytics queries into a hardware description. Deployed on an FPGA, the queries can be executed 60 times faster on average compared to a multi-threaded software implementation. The performance has been evaluated on two generations of high-end server systems including two generations of FPGAs, demonstrating the performance gains from advanced technology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07437315
Volume :
111
Database :
Academic Search Index
Journal :
Journal of Parallel & Distributed Computing
Publication Type :
Academic Journal
Accession number :
125862278
Full Text :
https://doi.org/10.1016/j.jpdc.2017.05.015