RAPS: Restore-Aware Policy Selection for STT-MRAM-Based Main Memory under Read Disturbance

As an important non-volatile memory technology, STTMRAM is widely considered as a universal memory solution in current 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 a need of restoring data back to memory after each read operation. These extra restores greatly change the timing scenarios that conventional designs are optimized for. As a result, directly adopting conventional, restore-agnostic memory management techniques may lead to suboptimal designs for STT-MRAM. In this work, 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 the open-and close-page 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 the conventional page-closure policies.