Expanding Logical Space Freely: A Memory-efficient Mapping Table Design for Compressional SSDs
Compressional SSDs can be a mixed blessing. While they offer users expanded logical space beyond the physical capacity, they complicate the Flash Translation Layer (FTL) design by requiring a larger Logical-to-Physical (L2P) address mapping, which places a heavier burden on the limited in-SSD memory, leading to a degraded I/O performance. In this paper, we aim to reduce the memory footprint of the L2P mapping table in compressional SSDs by proposing a novel N-to-1 L2P mapping table design that consolidates multiple logical entries into a single entry. This approach eliminates the duplication of physical page numbers when a physical page contains several compressed logical pages. To accommodate the dynamic compression ratios of real-world workloads, we introduce promotion and demotion that enable mapping table entries to migrate between pages with different compression ratios. Additionally, to address the issue of partial invalidation-where some compressed logical pages within a physical page are invalid due to the N-to-1 mapping-we present a compression-aware garbage collection algorithm aimed at minimizing the number of copy operations for partially invalid physical pages. We have implemented our design in MQsim, a widely used SSD simulator, and have conducted a series of experiments to evaluate the effectiveness of the proposed techniques. The results demonstrate that our approach significantly reduces the mapping table size in compressional SSDs, leading to an improved mapping table cache hit ratio and a reduced I/O latency compared to traditional compressional SSDs.
Authors
- Zelin Du (ORCID: https://orcid.org/0000-0002-6496-2669)
- Zixuan Huang (ORCID: https://orcid.org/0009-0006-7121-6775)
- Kecheng Huang (ORCID: https://orcid.org/0009-0003-7204-0984)
- Zili Shao (ORCID: https://orcid.org/0000-0002-2173-2847)
- Tianyu Wang (ORCID: https://orcid.org/0000-0001-9803-1339)
Institutions
- Chinese University of Hong Kong (HK)
- Shenzhen University (CN)
Publication Details
- Published
- 2025-06-22
- DOI
- https://doi.org/10.1109/dac63849.2025.11132583
- Primary Topic
- Advanced Data Storage Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00