RDA: A Read-Request Driven Adaptive Allocation Scheme for Improving SSD Performance

The parallel operation technology plays a pivotal role in enhancing performance of 3D NAND flash-based SSDs. High-parallel distribution of consecutive pages places the pages on different parallel units, thereby improving the parallelism and throughput of read requests. However, the high-parallel distribution generates two problems: 1) aggravating data fragmentation and 2) exacerbating the impact of garbage collection on latency. Moreover, small reads only require a few parallel units, and thus the high-parallel distribution is redundant for the requests. To address this issue, we propose a read-request driven adaptive allocation scheme called RDA to bolster SSD performance by adaptively adjusting the parallel distribution of consecutive pages. The RDA scheme employs the size of historical read requests to gauge the level of parallelism for write requests with varying sizes. Then, RDA allocates the logical pages of writes to distinct parallel units according to the parallelism of the requests. In doing so, RDA effectively mitigates the performance degradation of SSDs caused by redundant parallel distribution, while preserving the parallelism of read requests. We compare RDA with the three state-of-art schemes Amphibian, SOML, and Preemptive GC in terms of GC-blocked read requests, GC counts, and read response time under eight real-world workloads. The experimental results unveil that compared with the existing schemes, RDA revamps the GC-blocked read requests, GC counts, and read response time by averages of 20.6%, 7.8%, and 15.8%, respectively.