The amount of data is increasing explosively, and many in-memory-based database management systems have been developed to efficiently manage data in real time. However, these in-memory databases mainly use DRAM main memory, which raises problems due to price and energy consumption. To mitigate these problems, we propose a hybrid main memory structure based on DRAM and NAND flash that is cheaper and consumes less energy than DRAM. The proposed system incorporates a prefetching mechanism in last-level cache based on regression analysis to handle irregular memory access from the in-memory application and a migration technique based on clustering between DRAM and NAND flash to mitigate NAND flash slow access latency, which could otherwise significantly degrade system performance. We experimentally confirmed approximately 58% and 51% execution time and energy improvement compared with using DRAM alone. We also compared existing prefetching models without migration to evaluate the proposed prefetching and migration techniques and showed approximately 24% and 23% improvement for execution time and an energy consumption, respectively.
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea funded by the Korea government (MSIT) (NRF-2019R1A2C1008716). Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This work was supported by the National Research Foundation of Korea funded by the Korea government (MSIT) (NRF-2019R1A2C1008716).
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Information Systems
- Hardware and Architecture