A Correlation-Aware Page-Level FTL to Exploit Semantic Links in Workloads

摘要

NAND Flash based Solid State Disks (SSDs) are gaining tremendous popularity in today's storage market due to their unique erase-before-write feature. The Flash Translation Layer (FTL) in the SSDs redirects the incoming writes to a free physical address and manages a logical to physical address mapping table. However, this induces significant performance degradation to the SSDs. One of the main reasons is that current cache management in FTLs is mainly optimized for the temporal or spatial locality. However, because of multiple levels of data buffers in the whole storage architecture, the locality of internal disk I/O is relatively low. What's more, the increasing capacity of SSD not only generates large mapping tables, but also imposes high pressure on the efficiency of page-level address mapping. To overcome this limitation, we propose Correlation-Aware Page-level FTL, a.k.a CPFTL, which exploits I/O correlations in the workloads. In CPFTL, we develop a correlation-aware mapping table based on the correlation in read operations. We then build a correlation prediction table to support fast mapping entry lookup in the correlation-aware mapping table. Finally, we split read and write caches and build a skew-aware dirty entry index to improve the cache hit ratio and reduce the garbage collection overhead. Our emulator and prototype are open-sourced at: https://github.com/janzhou/SSD-Emulator. The experimental results show that CPFTL can reduce the average response time by 63.4 percent for read dominant workloads and 32.9 percent for transaction workloads.