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arXiv 2302.03591cs.CRcs.AR
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DSAC:利用DRAM内随机与近似计数算法实现低成本RowHammer缓解

DSAC: Low-Cost RowHammer Mitigation Using In-DRAM Stochastic and Approximate Counting Algorithm

Seungki Hong, Dongha Kim, Jaehyung Lee, Reum Oh, Changsik Yoo, Sangjoon Hwang, Jooyoung Lee

AI总结:

针对RowBleed与RowHammer位翻转,本文提出时间加权计数及DSAC随机近似计数保护机制,并以最大干扰指标验证其较现有计数器算法降低133倍。

摘要:

本文阐述了两类由行激活引发的位翻转的基本机制,并提出了DRAM内保护技术。RowBleed发生在受害行因相邻攻击行长时间激活所引起的晶体管阈值电压降低而出现电荷泄漏时。因此,本文提出用于缓解RowBleed的时间加权计数(Time-Weighted Counting),该方法为激活持续时间更长的行分配更大的计数器权重。另一方面,RowHammer发生在受害行因相邻攻击行频繁激活而出现电子注入时。类似地,Extended RowHammer(即受害行位于距攻击行两行之外的现象)同样由相邻攻击行频繁激活导致的电子注入引起。因此,准确检测攻击行至关重要。为此,本文提出名为DSAC(in-DRAM Stochastic and Approximate Counting algorithm,DRAM内随机与近似计数算法)的RowHammer缓解算法,该算法利用根据旧行计数进行调整的替换概率。本文引入了称为最大干扰(Maximum Disturbance)的RowHammer保护指标,用于衡量观察期内行激活的最大累积次数。实验结果表明,与最先进的基于计数器的算法相比,DSAC能够将最大干扰降低133倍。

英文摘要:

This paper provides the fundamental mechanisms of two types of row activation-induced bit flips and proposes in-DRAM protection techniques. RowBleed occurs when a victim row experiences charge leakage due to transistor's threshold voltage lowering induced by long activation of a neighboring aggressor row. Therefore, this paper proposes Time-Weighted Counting for RowBleed mitigation, which assigns greater counter weights to rows that are activated for longer durations. On the other hand, RowHammer occurs when a victim row experiences electron injection due to frequent activation of a neighboring aggressor row. Similarly, Extended RowHammer, the phenomenon where victim rows are two rows beyond aggressor rows, is also caused by electron injection due to frequent activation of a neighboring aggressor row. Consequently, accurate detection of aggressor rows is crucial. Therefore, this paper proposes RowHammer mitigation algorithm named DSAC (in-DRAM Stochastic and Approximate Counting algorithm), which utilizes a replacement probability that adjusts based on the count of the old row. This paper introduces a RowHammer protection index called Maximum Disturbance, which measures the maximum accumulated number of row activations within an observation period. The experimental results demonstrate that DSAC can achieve 133x lower Maximum Disturbance than the state-of-the-art counter-based algorithm.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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