- By:
- Lee, Sangyun; Byeon, Sungjin; Soon, Hwang ; Park, Jaewan; Hwang, Joo-Young; Han, Junyoung; González, Javier; Khan, Awais ; Kim, Youngjae
- Page Number:
- 1375-1384
- Book Title:
- SC Workshops '25: Proceedings of the SC '25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis
- Publication Date:
- March 12, 2026
- Publisher Location:
- Association for Computing Machinery, St Louis, Missouri, United States of America
- Conference Name:
- The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC '25)
- Conference Location:
- St Louis, Missouri, United States of America
- Conference Sponsor:
- SIGHPC
- View DOI Listing:
- https://doi.org/10.1145/3731599.3767511
Abstract
In-Memory Databases (IMDBs) are widely used with HPC applications to manage transient data, often using snapshot-based persistence for backups. Redis, a representative IMDB, employs both snapshot and Write-Ahead Log (WAL) mechanisms, storing data on persistent devices via the traditional kernel I/O path. This method incurs syscall overhead, I/O contention between processes, and SSD garbage collection (GC) delays. To address these issues, we propose SlimIO, which adopts I/O passthru to minimize syscall overhead and inter-process I/O interference. Additionally, it leverages Flexible Data Placement (FDP) SSDs as backup storage to avoid performance degradation from SSD GC. Experimental results show that SlimIO reduces snapshot time by up to 25%, increases query throughput by up to 30% during non-snapshot periods, and lowers 99.9%-ile latency by up to 50%. Furthermore, it achieves a write amplification factor (WAF) of 1.00, indicating no redundant internal writes, thus extending SSD lifespan.
