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

Research output: Contribution to journalArticlepeer-review

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 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 paper, 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.

Original languageEnglish
JournalIEEE Embedded Systems Letters
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Data reorganization
  • Data transfer
  • Databases
  • In-storage accelerator
  • Loading
  • Memory management
  • Multidimensional database.
  • Nonvolatile memory
  • Random access memory
  • Registers
  • Storage method

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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