P-OFTL: an object-based semantic-aware parallel flash translation layer

Abstract

With increased density and decreased price, flash memory has been widely used in storage systems for its low latency and low power features. However, traditional storage systems are designed and excessively optimized for magnetic disks, and the potential of flash memory is not brought into full play in the form of Solid State Drives (SSDs). In this paper, we propose p-OFTL, an object-based semantic-aware parallel flash translation layer (FTL). p-OFTL removes the mapping table in the FTL and directly manages the flash memory in file objects, which enables optimization of data layout in the flash using object semantics. While the removing of the mapping table improves system performance, a challenge remains to exploit the internal parallelism when maintaining the continuity of logical addresses in each object, which is essential for efficient garbage collection. To address this challenge, p-OFTL statically remaps the addresses by shifting the bits in the addresses, which spreads writes to different internal parallel units without another mapping table. Also, p-OFTL employs a semantic-aware data grouping algorithm to group data pages by trading off the hot-cold clustering for the continuity of logical addresses, so as to reduce the page movement in garbage collection. Experiments show that p-OFTL improves system performance by 4.0% ~ 10.3% and reduces garbage collection overhead by 15.1% ~ 32.5% in semantic-aware data grouping compared to those in semantic-unaware data grouping algorithms.