MIRZA: Efficiently Mitigating Rowhammer with Randomization and ALERT

In-DRAM Rowhammer mitigation requires three resources: space (to track aggressor rows), time (to perform mitigation), and energy (to refresh victim rows). An ideal in-DRAM mitigation must minimize all three overheads. Recent randomized trackers, such as MINT, can perform tracking with negligible storage overheads. However, they perform mitigation proactively and frequently, which incurs significant performance and energy overheads at low thresholds. Recently, JEDEC introduced Per-Row Activation Counters (PRAC) and ALERT Back Off (ABO) protocol to obtain the time for mitigation reactively, as needed. While PRAC+ABO minimizes the time and energy overheads of mitigation, PRAC incurs significant changes to the DRAM array and significant performance overhead (6.5% on average) due to increased memory timings to update the PRAC counters. Our goal is to develop an efficient in-DRAM mitigation that has low storage, performance, and energy overheads. Our paper proposes MIRZA, the first low-cost reactive in-DRAM mitigation. MIRZA relies on MINT to track aggressor rows. However, instead of proactively doing mitigation at regular intervals (via REF or RFM), MIRZA uses ABO to reactively obtain the time required for mitigation. To avoid frequent ABO, MIRZA employs Coarse-Grained Filtering to disable mitigations if the activation count is below a certain Filtering Threshold. To tolerate a threshold of 1K, MIRZA requires a storage overhead of only 196 bytes of SRAM per bank. Compared to MINT, MIRZA reduces the mitigation overheads by 28.5×. Compared to PRAC, MIRZA has 45× lower area overheads and negligible slowdown (0.36% average slowdown vs. 6.5% for PRAC).