Mitigating and Tolerating Read Disturbance in STT-MRAM-Based Main Memory via Device and Architecture Innovations

As an important nonvolatile memory technology, spin transfer torque magnetoresistive RAM (STT-MRAM) is widely considered as a universal memory solution for future processors. Employing STT-MRAM as the main memory offers a wide variety of benefits, but also results in unique design challenges. In particular, read disturbance characterizes accidental data corruption in STT-MRAM after it is read, leading to the need of restoring data back to memory after each read operation. In this paper, we propose both device and architecture innovations to mitigate and tolerate read disturbance. First, we quantitatively demonstrate the relationship between read disturbance and key device parameters, conducting a number of read disturbance mitigation schemes. These device-level schemes turn out to be effective in reducing the read disturbance probability, but come with costs on other design metrics. Consequently, we further propose a restore-aware memory controller design at the architecture level to tolerate read disturbance. Since the extra restores incurred by read disturbance greatly change the timing scenarios that conventional memory controllers were optimized for, directly adopting restore-agnostic DRAM memory management techniques will lead to suboptimal designs for STT-MRAM. Therefore, we propose restore-aware policy selection (RAPS), a dynamic and hybrid row buffer management scheme that factors in the inevitable data restores in STT-MRAM-based main memory. RAPS monitors the row buffer hit rate at run time, dynamically switching between two static page-closure policies. By factoring in restores, RAPS accurately captures the optimal design points, achieving optimal policy selections at run time. Our experimental results show that RAPS significantly improves system performance and energy efficiency compared to conventional page-closure policies.