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CSGC: Collaborative File System Garbage Collection with Computational Storage
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DOI：10.1007/978-3-031-99857-7_11.png)
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Abstract
En 中文
Garbage collection (GC) in log-structured file systems (LFS) is known to cause performance degradation, particularly in writeintensive scenarios. Existing approaches, such as in-storage migration and hotness-based grouping, aim to enhance GC efficiency. However, these approaches lack effective host-device collaboration, leading to either excessive communication overhead from inefficient task offloading or severe write amplification due to the log-on-log issue. We present CSGC, a host-device collaborative GC approach that utilizes computational storage device (CSD) to optimize GC efficiency. CSGC uses a pipelined CSD-offloaded migration framework with metadata piggybacking to reduce host-device communication overhead, along with a separate flash translation layer (sFTL) to preserve data hotness and mitigate write amplification. Our evaluations using F2FS and Daisy+ OpenSSD show that CSGC significantly improves GC performance, contributing to up to 3.6.x and 1.9.x speedup in I/O throughput over vanilla F2FS and IPLFS respectively.
Keywords:
Log-structured file system
Garbage collection
Computational storage device
Journal
E
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Papers:
24
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