Nemo: A Low-Write-Amplification Cache for Tiny Objects on Log-Structured Flash Devices

2026-03-10

AI Summary

This work addresses the inefficiency of existing flash caching systems under small-object workloads, which suffer from high application-level write amplification—even when deployed on log-structured devices such as Zoned Namespace (ZNS) SSDs. To overcome this limitation, the authors propose Nemo, a novel caching scheme that deliberately increases hash collisions to improve cache set occupancy, thereby reducing write amplification. Nemo further integrates a Bloom filter-based index to minimize memory overhead and employs a hybrid hotness-tracking mechanism to maintain low miss rates while enhancing memory efficiency. Experimental results demonstrate that, when implemented on ZNS SSDs, Nemo achieves a synergistic optimization of low write amplification, high memory efficiency, and low cache miss rates.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Search and Optimization: Distributed Search
• Data Mining & Knowledge Management: Data Compression

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Security and Privacy: Large-scale security measurements

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 without losing memory efficiency. Experimental results show that Nemo simultaneously achieves three key objectives for flash cache: low write amplification, high memory efficiency, and low miss ratio.

Problem

• write amplification
• tiny objects
• flash cache
• log-structured flash
• application-level write amplification

Innovation

• write amplification
• log-structured flash
• tiny objects
• bloom filter indexing
• hybrid hotness tracking