Workload-aware Data-eviction Self-adjusting System of Multi-SCM Storage to Resolve Trade-off between SCM Data-retention Error and Storage System Performance

Abstract

Storage Class Memories (SCMs) are used as non-volatile (NV) cache memory as well as storage. Multi-SCM storage with two types of SCMs, M-SCM (fast but small capacity memory-type SCM) and S-SCM (slow but large capacity storage-type SCM), has been proposed. In Multi-SCM storage, M-SCM works as NV-cache of S-SCM based storage. M-SCM such as MRAM is fast but may suffer from thermal instabilities and cause data-retention errors at high temperature. Therefore, data in M-SCM should be evicted to S-SCM at short interval before exceeding acceptable data-retention time. However, in case of short interval eviction, frequent data eviction from M-SCM to S-SCM severely degrades the storage system performance. To resolve this trade-off between data-retention reliability and the storage system performance, this paper proposes workload-aware data-eviction self-adjusting system. Proposed system is composed of Access Frequency Monitor (Proposal 1) and Evict Interval Adjustment (Proposal 2). Proposal 1 observes the access frequency of evicted data that directly affects data-retention time of M-SCM. By referring to the results of Proposal 1, Proposal 2 automatically changes the data-eviction interval so that long retention data are moved immediately to S-SCM and the storage system performance can be improved. As a result, maximum data-retention time of M-SCM decreases by 83%, and the storage system performance increases by 5.9 times. Moreover, the acceptable endurance increases by 103 times. Finally, measured data-retention errors and memory cell area decrease by 79% and 5.7%, respectively.