학술논문

Column-Oriented Database Acceleration Using FPGAs
Document Type
Conference
Source
2019 IEEE 35th International Conference on Data Engineering (ICDE) Data Engineering (ICDE), 2019 IEEE 35th International Conference on. :686-697 Apr, 2019
Subject
Computing and Processing
Engines
Acceleration
Field programmable gate arrays
Data mining
Databases
Dictionaries
Filtering
Column-oriented Database
FPGA
Language
ISSN
2375-026X
Abstract
The in-memory system is promising for improving the performance of column-oriented database management systems (DBMSs). However, in comparison with NAND-flash-based solid-state drives (SSDs), dynamic random access memories (DRAMs) are around ten times more expensive and tens to thousands of times more energy inefficient. To overcome this drawback, we developed a column-oriented DBMS and a field-programmable-gate-array-based acceleration engine. We integrated them in FCAccel, our prototype system. The acceleration engine accelerates data extraction from SSDs for SQL processing. We compared the performance of FCAccel with that of MonetDB, Impala and PostgreSQL. Performance was evaluated under the conditions that MonetDB and Impala stored all data in DRAMs and FCAccel stored all data in SSDs. With regard to data extraction, the performance of FCAccel ranged from 0.77 to 1.79 times in comparison with that of MonetDB and from 4.10 to 23.4 times in comparison with that of Impala. These experimental results imply that the acceleration engine can remove the necessity to store all data in DRAMs.