DRAM chips are increasingly more vulnerable to read disturbance phenomena (e.g., RowHammer and RowPress), where repeatedly accessing DRAM rows causes bitflips in nearby rows due to DRAM density scaling. Even though many prior works develop various RowHammer solutions, these solutions incur non-negligible and increasingly higher system performance, energy, and hardware area overheads as RowHammer vulnerability worsens.
In this talk, we will present our recent works on 1) understanding DRAM read disturbance in modern high bandwidth memory (HBM) chips, along with the open source infrastructure that enables experimental studies on state-of-the-art DRAM chips, and 2) performance-, energy-, and area-efficient system-level solutions to read disturbance. First, we describe the results of a detailed experimental analysis of read disturbance in six real HBM2 chips. We show that (1) the read disturbance vulnerability significantly varies between different HBM2 chips and between different components (e.g., 3D-stacked channels) inside a chip, (2) DRAM rows at the end and in the middle of a bank are more resilient to read disturbance, (3) fewer additional activations are sufficient to induce more read disturbance bitflips in a DRAM row if the row exhibits the first bitflip at a relatively high activation count, and (4) a modern HBM2 chip implements undocumented read disturbance defenses that track potential aggressor rows based on how many times they are activated. We also briefly describe the infrastructure that enabled the discoveries we made in our study on read disturbance in high bandwidth memory chips along with those made in multiple recent works that investigate read disturbance in real DRAM chips (e.g., RowPress).
Second, we introduce ABACuS, a new low-cost hardware-counter-based RowHammer mitigation technique that performance-, energy-, and area-efficiently scales with worsening RowHammer vulnerability. 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. At very low RowHammer thresholds (where only 125 activations cause a bitflip), ABACuS induces small system performance and DRAM energy overhead, and outperforms and takes up smaller chip area than the state-of-the-art mitigation techniques (Hydra and Graphene).
Ataberk Olgun is a 3rd year PhD student at ETH Zurich. His broad research interests include designing secure, high-performance, and energy-efficient DRAM architectures. Especially with worsening RowHammer vulnerability, it is increasingly difficult to design new DRAM architectures that satisfy all three characteristics. His current research focuses on i) deeply understanding and ii) efficiently mitigating the RowHammer vulnerability in modern systems.