Hot/cold clustering for page mapping in NAND flash memory

Abstract

NAND flash memory, which is widely used as a storage medium for mobile devices because of its lightweight, shock-resistant, silent, and energy-efficient characteristics, lacks an over-write operation. Therefore, NAND-based storage devices deploy a flash translation layer (FTL) to emulate the over-write operation with out-of-place updates. However, as out-of-place updates write data to new unwritten spaces, clean spaces eventually become scarce. This initiates a garbage collection process that accompanies several NAND writes and erases. Thus, it is important to reduce the latency and frequency of garbage collection, which is a primary aim of the present work. The central idea is to cluster hot and cold data separately to reduce the number of valid pages in a victim block at the time of garbage collection. Reducing the number of valid pages of the victim block contributes to the reduction of both the latency and frequency of the garbage collection process. Trace-driven simulations show that the proposed hot/cold clustering improves write throughput by up to 18%.