IDRA: An In-Storage Data Reorganization Accelerator for Multidimensional Databases
- Authors
- Kim, Seon Young; Chung, Yon Dohn; Chung, 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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Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
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