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IDRA: An In-Storage Data Reorganization Accelerator for Multidimensional Databases

Authors
Kim, Seon YoungChung, Yon DohnChung, Sung Woo
Issue Date
12월-2021
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Data reorganization; in-storage accelerator; multidimensional database; storage method
Citation
IEEE EMBEDDED SYSTEMS LETTERS, v.13, no.4, pp.198 - 201
Indexed
SCIE
SCOPUS
Journal Title
IEEE EMBEDDED SYSTEMS LETTERS
Volume
13
Number
4
Start Page
198
End Page
201
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/135623
DOI
10.1109/LES.2021.3066057
ISSN
1943-0663
Abstract
In the multidimensional databases, various storage methods for the main memory have been proposed for efficient data processing. On the other hand, storage devices such as SSD still leverage the conventional row-oriented storage method to avoid complicated operating system modification. Since there is a difference in storage methods between the main memory and storage device, it is necessary to reorganize the data between them. However, data reorganization in the conventional CPU-based systems causes a long latency due to a large number of memory accesses. In addition, it also causes high dynamic power consumption of a CPU. In this letter, we propose an in-storage data reorganization accelerator for multidimensional databases (IDRA). We place the IDRA in an SSD to reorganize data on the fly while loading it into the main memory without intervention of the CPU. In our evaluation on the off-the-shelf system (not simulation), the IDRA-based system improves the performance by 78.6% and reduces the system-wide energy by 30.3%, on average, compared to the conventional CPU-based system.
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