Mitigating Voltage Drop in Resistive Memories by Dynamic RESET Voltage Regulation and Partition RESET
Farzaneh Zokaee, Lei Jiang
摘要
The emerging resistive random access memory (ReRAM) technology has been deemed as one of the most promising alternatives to DRAM in main memories, due to its better scalability, zero cell leakage and short read latency. The cross-point (CP) array enables ReRAM to obtain the theoretical minimum 4F^2 cell size by placing a cell at the cross-point of a word-line and a bit-line. However, ReRAM CP arrays suffer from large sneak current resulting in significant voltage drop that greatly prolongs the array RESET latency. Although prior works reduce the voltage drop in CP arrays, they either substantially increase the array peripheral overhead or cannot work well with wear leveling schemes. In this paper, we propose two array micro-architecture level techniques, dynamic RESET voltage regulation (DRVR) and partition RESET (PR), to mitigate voltage drop on both bit-lines and word-lines in ReRAM CP arrays. DRVR dynamically provides higher RESET voltage to the cells far from the write driver and thus encountering larger voltage drop on a bit-line, so that all cells on a bit-line share approximately the same latency during RESETs. PR decides how many and which cells to reset online to partition the CP array into multiple equivalent circuits with smaller word-line resistance and voltage drop. Because DRVR and PR greatly reduce the array RESET latency, the ReRAM-based main memory lifetime under the worst case non-stop write traffic significantly decreases. To increase the CP array endurance, we further upgrade DRVR by providing lower RESET voltage to the cells suffering from less voltage drop on a word-line. Our experimental results show that, compared to the combination of prior voltage drop reduction techniques, our DRVR and PR improve the system performance by 11.7% and decrease the energy consumption by 46% averagely, while still maintaining >10-year main memory system lifetime.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
引用它的顶会 Paper1
问问它们各自怎么用它相关 Paper
- Realizing Extreme Endurance Through Fault-aware Wear Leveling and Improved ToleranceJiangwei Zhang, Chong Wang, Zhenhua Zhu, Donald Kline 等HPCA 2023 · 被引用 5 次
- CDAR-DRAM: An In-situ Charge Detection and Adaptive Data Restoration DRAM Architecture for Performance and Energy Efficiency ImprovementChuxiong Lin, Weifeng He, Yanan Sun, Zhigang Mao 等DAC 2021 · 被引用 6 次
- CLR-DRAM: A Low-Cost DRAM Architecture Enabling Dynamic Capacity-Latency Trade-OffHaocong Luo, Taha Shahroodi, Hasan Hassan, Minesh Patel 等ISCA 2020 · 被引用 64 次
- Understanding RowHammer Under Reduced Refresh Latency: Experimental Analysis of Real DRAM Chips and Implications on Future SolutionsYahya Can Tugrul, A. Giray Yaglikçi, Ismail Emir Yüksel, Ataberk Olgun 等HPCA 2025 · 被引用 10 次
- PF-DRAM: A Precharge-Free DRAM StructureNezam Rohbani, Sina Darabi, Hamid Sarbazi-AzadISCA 2021 · 被引用 16 次
