کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4956728 | 1444590 | 2017 | 23 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
AxleDB: A novel programmable query processing platform on FPGA
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
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چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microprocessors and Microsystems - Volume 51, June 2017, Pages 142-164
Journal: Microprocessors and Microsystems - Volume 51, June 2017, Pages 142-164
نویسندگان
Behzad Salami, Gorker Alp Malazgirt, Oriol Arcas-Abella, Arda Yurdakul, Nehir Sonmez,