1. Giving Text Analytics a Boost.
- Author
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Polig, Raphael, Atasu, Kubilay, Chiticariu, Laura, Hagleitner, Christoph, Hofstee, H. Peter, Reiss, Frederick R., Zhu, Huaiyu, and Sitaridi, Eva
- Subjects
- *
COMPUTER software research , *COMPUTER architecture , *BANDWIDTH research , *BIG data - Abstract
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. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
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