REMUS: Efficient Multi-Request Scheduling in Computational Storage Devices
Huang, Yun Bai, Shuhan Su, Qiang Yen, Heng-Lin Guan, Nan Kuo, Tei-Wei Liu, Xue Xue, Chun Jason
Huang, Yun
Bai, Shuhan
Su, Qiang
Yen, Heng-Lin
Guan, Nan
Kuo, Tei-Wei
Liu, Xue
Xue, Chun Jason
Supervisor
Department
Computer Science
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
Data-intensive applications benefit from offloading data processing to storage devices with embedded cores, typically Computational Storage Device (CSD). Co-locating requests from different applications to one CSD offers better performance and power efficiency than dedicating CSDs to a single application. However, current CSD scheduling frameworks fail to handle the contention in CPU, Flash I/O and buffer due to mismatching of resources and the requests, leading to sub-optimal performance. This paper proposes REMUS, a CSD scheduling framework handling multiple requests for CSD platforms with multiple homogeneous cores. The key idea of REMUS is to allocate the workload to multiple cores according to the distribution of the Logical Block Address (LBA) of the requests and mitigate stall time by sorting requests based on their urgency of demand for resources, where urgency is quantified by the current remaining buffer capacity of the requests. Furthermore, a buffer allocation scheme is proposed to avoid programs that exclusively occupy the resources. We conduct experiments on both a simulator and a real CSD platform. The experiment results show that REMUS improved throughput by 1.51× on the simulator and 1.39× on the real platform on average compared to the baselines.
Citation
Y. Huang et al., "REMUS: Efficient Multi-Request Scheduling in Computational Storage Devices," 2025 IEEE 31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), Singapore, Singapore, 2025, pp. 150-157, doi: 10.1109/RTCSA66114.2025.00024.
Source
2026 IEEE 31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
Conference
31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
Keywords
Computational storage, Scheduling
Subjects
Source
31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
Publisher
IEEE