We introduce ABACuS, a new low-cost hardware-counter-based RowHammer mitigation technique that performance-, energy-, and area-efficiently scales with worsening RowHammer vulnerability. We observe that both benign workloads and RowHammer attacks tend to access DRAM rows with the same row address in multiple DRAM banks at around the same time. Based on this observation, ABACuS's key idea is to use a single shared row activation counter to track activations to the rows with the same row address in all DRAM banks. Unlike state-of-the-art RowHammer mitigation mechanisms that implement a separate row activation counter for each DRAM bank, ABACuS implements fewer counters (e.g., only one) to track an equal number of aggressor rows. Our evaluations show that ABACuS securely prevents RowHammer bitflips at low performance/energy overhead and low area cost. We compare ABACuS to four state-of-the-art mitigation mechanisms. At a near-future RowHammer threshold of 1000, ABACuS incurs only 0.58% (0.77%) performance and 1.66% (2.12%) DRAM energy overheads, averaged across 62 single-core (8-core) workloads, requiring only 9.47 KiB of storage per DRAM rank. At the RowHammer threshold of 1000, the best prior low-area-cost mitigation mechanism incurs 1.80% higher average performance overhead than ABACuS, while ABACuS requires 2.50X smaller chip area to implement. At a future RowHammer threshold of 125, ABACuS performs very similarly to (within 0.38% of the performance of) the best prior performance- and energy-efficient RowHammer mitigation mechanism while requiring 22.72X smaller chip area. ABACuS is freely and openly available at https://github.com/CMU-SAFARI/ABACuS.

翻译：我们提出ABACuS——一种基于硬件计数器的新型低成本RowHammer缓解技术，该技术能够随RowHammer漏洞恶化趋势以性能、能耗和面积高效的方式扩展。我们观察到，良性工作负载和RowHammer攻击均倾向于在多个DRAM存储体中大致同时访问相同行地址的DRAM行。基于此观察，ABACuS的核心思想是使用单个共享行激活计数器，追踪所有DRAM存储体中相同行地址对应的行的激活情况。与现有最先进的RowHammer缓解机制（为每个DRAM存储体分别实现独立行激活计数器）不同，ABACuS通过更少的计数器（例如仅一个）来追踪相同数量的攻击行。评估表明，ABACuS能以较低的性能/能耗开销和面积成本安全地防止RowHammer比特翻转。我们将ABACuS与四种最先进的缓解机制进行对比。在近未来RowHammer阈值1000下，ABACuS在62个单核（八核）工作负载上的平均性能开销仅为0.58%（0.77%），DRAM能耗开销为1.66%（2.12%），每个DRAM rank仅需9.47 KiB存储空间。在阈值1000下，最佳现有低面积成本缓解机制的平均性能开销比ABACuS高1.80%，而ABACuS的实现芯片面积仅为前者的2.50倍。在未来的RowHammer阈值125下，ABACuS的性能与现有最佳性能和能效缓解机制极其接近（性能差异在0.38%以内），但所需芯片面积仅为后者的22.72倍。ABACuS开源代码详见https://github.com/CMU-SAFARI/ABACuS。