Hydra: enabling low-overhead mitigation of row-hammer at ultra-low thresholds via hybrid tracking

Moinuddin K. Qureshi, Aditya Rohan, Gururaj Saileshwar, Prashant J. Nair
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引用次数: 22

Abstract

DRAM systems continue to be plagued by the Row-Hammer (RH) security vulnerability. The threshold number of row activations (TRH) required to induce RH has reduced rapidly from 139K in 2014 to 4.8K in 2020, and TRH is expected to reduce further, making RH even more severe for future DRAM. Therefore, solutions for mitigating RH should be effective not only at current TRH but also at future TRH. In this paper, we investigate the mitigation of RH at ultra-low thresholds (500 and below). At such thresholds, state-of-the-art solutions, which rely on SRAM or CAM for tracking row activations, incur impractical storage overheads (340KB or more per rank at TRH of 500), making such solutions unappealing for commercial adoption. Alternative solutions, which store per-row metadata in the addressable DRAM space, incur significant slowdown (25% on average) due to extra memory accesses, even in the presence of metadata caches. Our goal is to develop scalable RH mitigation while incurring low SRAM and performance overheads. To that end, this paper proposes Hydra, a Hybrid Tracker for RH mitigation, which combines the best of both SRAM and DRAM to enable low-cost mitigation of RH at ultra-low thresholds. Hydra consists of two structures. First, an SRAM-based structure that tracks aggregated counts at the granularity of a group of rows, and is sufficient for the vast majority of rows that receive only a few activations. Second, a per-row tracker stored in the DRAM-array, which can track an arbitrary number of rows, however, to limit performance overheads, this tracker is used only for the small number of rows that exceed the tracking capability of the SRAM-based structure. We provide a security analysis of Hydra to show that Hydra can reliably issue a mitigation within the specified threshold. Our evaluations show that Hydra enables robust mitigation of RH, while incurring an SRAM overhead of only 28 KB per-rank and an average slowdown of only 0.7% (at TRH of 500).
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Hydra:通过混合跟踪,在超低阈值下实现低开销的行锤缓解
DRAM系统继续受到Row-Hammer (RH)安全漏洞的困扰。诱导RH所需的行激活阈值(TRH)从2014年的139K迅速降低到2020年的4.8K,并且TRH预计将进一步降低,使未来DRAM的RH更加严重。因此,缓解RH的解决方案不仅应该对当前的TRH有效,而且应该对未来的TRH有效。在本文中,我们研究了在超低阈值(500及以下)下RH的缓解。在这样的阈值下,依靠SRAM或CAM来跟踪行激活的最先进的解决方案会产生不切实际的存储开销(TRH为500时,每个秩的存储开销为340KB或更多),使得此类解决方案不适合商业采用。在可寻址的DRAM空间中存储每行元数据的替代解决方案,即使在存在元数据缓存的情况下,也会由于额外的内存访问而导致显著的减速(平均25%)。我们的目标是开发可扩展的RH缓解,同时降低SRAM和性能开销。为此,本文提出了Hydra,一种用于RH缓解的混合跟踪器,它结合了SRAM和DRAM的优点,可以在超低阈值下实现低成本的RH缓解。九头蛇由两个结构组成。首先,基于sram的结构可以在一组行的粒度上跟踪聚合计数,并且对于只接收少量激活的绝大多数行已经足够了。第二种是存储在dram阵列中的逐行跟踪器,它可以跟踪任意数量的行,但是,为了限制性能开销,这种跟踪器仅用于超出基于sram结构的跟踪能力的少数行。我们提供了Hydra的安全性分析,以表明Hydra可以在指定的阈值内可靠地发出缓解。我们的评估表明,Hydra能够有效地降低相对湿度,同时每rank的SRAM开销仅为28 KB,平均速度仅为0.7% (TRH为500时)。
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