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AxleDB: A novel programmable query processing platform on FPGA

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10.1016/j.micpro.2017.04.018
 
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hdl:2117/104440

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Salami, Behzad
Malazgirt, Gorker Alp
Arcas-Abella, Oriol
Yurdakul, Arda
Sonmez, Nehir
Document typeArticle
Defense date2017-06-01
PublisherElsevier
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
ProjectCOMPUTACION DE ALTAS PRESTACIONES VII (MINECO-TIN2015-65316-P)
Abstract
With the rise of Big Data, providing high-performance query processing capabilities through the acceleration of the database analytic has gained significant attention. Leveraging Field Programmable Gate Array (FPGA) technology, this approach can lead to clear benefits. In this work, we present the design and implementation of AxleDB: An FPGA-based platform that enables fast query processing for database systems by melding novel database-specific accelerators with commercial-off-the-shelf (COTS) storage using modern interfaces, in a novel, unified, and a programmable environment. AxleDB can perform a large subset of SQL queries through its set of instructions that can map compute-intensive database operations, such as filter, arithmetic, aggregate, group by, table join, or sort, on to the specialized high-throughput accelerators. To minimize the amount of SSD I/O operations required, AxleDB also supports hardware MinMax indexing for databases. We evaluated AxleDB with five decision support queries from the TPC-H benchmark suite and achieved a speedup from 1.8X to 34.2X and energy efficiency from 2.8X to 62.1X, in comparison to the state-of-the-art DBMS, i.e., PostgreSQL and MonetDB.
CitationSalami, B. [et al.]. AxleDB: A novel programmable query processing platform on FPGA. "Microprocessors and Microsystems", 1 Juny 2017, vol. 51, p. 142-164. 
URIhttp://hdl.handle.net/2117/104440
DOI10.1016/j.micpro.2017.04.018
ISSN0141-9331
Publisher versionhttp://www.sciencedirect.com/science/article/pii/S0141933117302181
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