Nemo: A Low-Write-Amplification Cache for Tiny Objects on Log-Structured Flash Devices
Xufeng Yang, Tingting Tan, Jingxin Hu, Congming Gao, Mingyang Liu, Tianyang Jiang, Jian Chen, Linbo Long, Yina Lv, Jiwu Shu

TL;DR
Nemo is a novel cache design for flash storage that reduces application-level write amplification while maintaining high memory efficiency and low miss ratios, especially for tiny-object workloads.
Contribution
It introduces a set-associative cache with increased hash collision probability, a bloom filter-based index, and hybrid hotness tracking to optimize flash cache performance.
Findings
Significantly reduces application-level write amplification.
Achieves high memory efficiency with low miss ratios.
Maintains low write amplification even with advanced log-structured SSDs.
Abstract
Modern storage systems predominantly use flash-based SSDs as a cache layer due to their favorable performance and cost efficiency. However, in tiny-object workloads, existing flash cache designs still suffer from high write amplification. Even when deploying advanced log-structured flash devices (e.g., Zoned Namespace SSDs and Flexible Data Placement SSDs) with low device-level write amplification, application-level write amplification still dominates. This work proposes Nemo, which enhances set-associative cache design by increasing hash collision probability to improve set fill rate, thereby reducing application-level write amplification. To satisfy caching requirements, including high memory efficiency and low miss ratio, we introduce a bloom filter-based indexing mechanism that significantly reduces memory overhead, and adopt a hybrid hotness tracking to achieve low miss ratio…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Data Storage Technologies · Parallel Computing and Optimization Techniques · Caching and Content Delivery
