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Retention-Aware DRAM Auto-Refresh Scheme for Energy and Performance Efficiency

Department of Information and Computer Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan
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Micromachines 2019, 10(9), 590; https://doi.org/10.3390/mi10090590
Received: 30 July 2019 / Revised: 4 September 2019 / Accepted: 6 September 2019 / Published: 8 September 2019
(This article belongs to the Section A:Physics)
Dynamic random access memory (DRAM) circuits require periodic refresh operations to prevent data loss. As DRAM density increases, DRAM refresh overhead is even worse due to the increase of the refresh cycle time. However, because of few the cells in memory that have lower retention time, DRAM has to raise the refresh frequency to keep the data integrity, and hence produce unnecessary refreshes for the other normal cells, which results in a large refresh energy and performance delay of memory access. In this paper, we propose an integration scheme for DRAM refresh based on the retention-aware auto-refresh (RAAR) method and 2x granularity auto-refresh simultaneously. We also explain the corresponding modification need on memory controllers to support the proposed integration refresh scheme. With the given profile of weak cells distribution in memory banks, our integration scheme can choose the most appropriate refresh technique in each refresh time. Experimental results on different refresh cycle times show that the retention-aware refresh scheme can properly improve the system performance and have a great reduction in refresh energy. Especially when the number of weak cells increased due to the thermal effect of 3D-stacked architecture, our methodology still keeps the same performance and energy efficiency. View Full-Text
Keywords: DRAM refresh; retention time; refresh interval; refresh cycle time; auto-refresh DRAM refresh; retention time; refresh interval; refresh cycle time; auto-refresh
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Cheng, W.-K.; Shen, P.-Y.; Li, X.-L. Retention-Aware DRAM Auto-Refresh Scheme for Energy and Performance Efficiency. Micromachines 2019, 10, 590.

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