Giving Text Analytics a Boost

• Published in: IEEE MICRO Vol. 34; no. 4; pp. 6 - 14
• Main Authors: Polig, Raphael, Atasu, Kubilay, Chiticariu, Laura, Hagleitner, Christoph, Hofstee, H. Peter, Reiss, Frederick R., Zhu, Huaiyu, Sitaridi, Eva
• Format: Journal Article
• Language: English
• Published: Los Alamitos IEEE 01.07.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accelerators; Bandwidth; Bandwidths; Big data; Communication; Communication systems; Computer architecture; Computer programs; Field programmable gate arrays; field-programmable gate array; Hardware; hardware accelerator; heterogeneous system; Instruction sets; Memory; Queries; Software; text analytics; Text mining; Text processing; Texts
• ISSN: 0272-1732; 1937-4143
• DOI: 10.1109/MM.2014.69

The amount of textual data has reached a new scale and continues to grow at an unprecedented rate. IBM's SystemT software is a powerful text-analytics system that offers a query-based interface to reveal the valuable information that lies within these mounds of data. However, traditional server architectures are not capable of analyzing so-called big data efficiently, despite the high memory bandwidth that is available. The authors show that by using a streaming hardware accelerator implemented in reconfigurable logic, the throughput rates of the SystemT's information extraction queries can be improved by an order of magnitude. They also show how such a system can be deployed by extending SystemT's existing compilation flow and by using a multithreaded communication interface that can efficiently use the accelerator's bandwidth.