A hardware compilation framework for text analytics queries

• Published in: Journal of parallel and distributed computing Vol. 111; pp. 260 - 272
• Main Authors: Polig, Raphael, Atasu, Kubilay, Giefers, Heiner, Hagleitner, Christoph, Chiticariu, Laura, Reiss, Frederick, Zhu, Huaiyu, Hofstee, Peter
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.01.2018
• Subjects: Accelerator; FPGA; Query compilation; Text analytics; Text analytics; Query compilation; FPGA; Accelerator
• ISSN: 0743-7315; 1096-0848
• DOI: 10.1016/j.jpdc.2017.05.015

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. •A complete hardware compilation framework is presented that transforms text analytics queries into a synthesizable hardware description.•The accelerator architecture is coherently integrated with a general purpose processor demonstrating an up to 60 times faster processing rate.•The performance of two generations of systems is evaluated demonstrating the improvements gained by advances in technology.