Hydra: enabling low-overhead mitigation of row-hammer at ultra-low thresholds via hybrid tracking
Hydra: enabling low-overhead mitigation of row-hammer at ultra-low thresholds via hybrid tracking
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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
DOI：
10.1145/3470496.3527421
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发表时间：
2022
期刊：
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通讯作者：
Prashant J. Nair
中科院分区：
文献类型：
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作者：
Moinuddin K. Qureshi;Aditya Rohan;Gururaj Saileshwar;Prashant J. Nair
DRAM系统继续受到Row-Hammer（RH）安全漏洞的困扰。引发RH所需的行激活阈值数（TRH）已从2014年的139 K迅速降至2020年的4.8K，预计TRH将进一步降低，使未来DRAM的RH更加严重。因此，缓解RH的解决方案不仅在当前的TRH下有效，而且在未来的TRH下也有效。在本文中，我们研究了在超低阈值（500及以下）下RH的缓解。在这样的阈值处，依赖于SRAM或CAM来跟踪行激活的最先进的解决方案招致不切实际的存储开销（在TRH为500时，每列340 KB或更多），使得这样的解决方案对于商业采用没有吸引力。在可寻址DRAM空间中存储每行元数据的替代解决方案由于额外的存储器访问而导致显著的减速（平均25%），即使在存在元数据缓存的情况下也是如此。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，能够以超低阈值低成本缓解RH。Hydra由两个结构组成。第一种是基于SRAM的结构，它以一组行的粒度跟踪聚合计数，并且对于只接收少量激活的绝大多数行来说是足够的。第二，存储在DRAM阵列中的逐行跟踪器，其可以跟踪任意数量的行，然而，为了限制性能开销，该跟踪器仅用于超过基于SRAM的结构的跟踪能力的少量行。我们提供了一个Hydra的安全分析表明，Hydra可以可靠地发出缓解在指定的阈值。我们的评估表明，Hydra能够稳健地缓解RH，同时每秩仅产生28 KB的SRAM开销，平均速度仅为0.7%（TRH为500）。
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).