EFM: Elastic Flash Management to Enhance Performance of Hybrid Flash Memory

Abstract

NAND-based flash memory has become a prevalent storage media due to its low access latency and high performance. By setting up different incremental step pulse programming (ISPP) values and threshold voltages, the tradeoffs between lifetime and access latency in NAND-based flash memory can be exploited. The existing studies that exploit the tradeoffs by using heuristic algorithms do not consider the dynamically changed access latency due to wearing-out, resulting in low access performance. In this paper, we proposed a new Elastic Flash Management scheme, called EFM, to manage data in hybrid flash memory, which consists of multiple physical regions with different read/write latencies according to their ISPP values and threshold voltages. EFM includes a Long-Term Classifier (LT-Classifier) and a Short-Term Classifier (ST-Classifier) to accurately track dynamically changed workloads by considering current quantitative differences of read/write latencies and workload access patterns. Moreover, a reduced effective wearing management is proposed to prolong the lifetime of flash memory by scheduling write-intensive workloads to the region with a reduced threshold voltage and the lowest write cost. Experimental results indicate that EFM reduces the average read/write latencies by about 54% - 296% and obtain 17.7% lifetime improvement on average compared to the existing studies.