EBIO: An Efficient Block I/O Stack for NVMe SSDs with Mixed Workloads
With the advent of high-performance Non-Volatile Memory Express (NVMe) SSD, the overhead caused by the storage software stack becomes a significant bottleneck for exploiting the potential of NVMe SSD. Recent I/O isolation approaches eliminate CPU switching, I/O interference, and lock contention for...
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Veröffentlicht in: | IEEE transactions on computer-aided design of integrated circuits and systems 2023-12, Vol.42 (12), p.1-1 |
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Zusammenfassung: | With the advent of high-performance Non-Volatile Memory Express (NVMe) SSD, the overhead caused by the storage software stack becomes a significant bottleneck for exploiting the potential of NVMe SSD. Recent I/O isolation approaches eliminate CPU switching, I/O interference, and lock contention for I/O queues by pinning I/O threads in isolated and dedicated I/O paths. However, they degrade the overall performance of mixed workloads with heterogeneous I/O demands. The I/O-intensive workloads issue multiple I/O requests and quickly fill up their dedicated I/O queues, resulting in I/O wait. On the contrary, the non-I/O-intensive workloads cannot deliver enough I/O requests to saturate their associated I/O queues. Moreover, frequent allocations and deallocations of I/O request objects expose a significant overhead for I/O-intensive workloads. In this paper, we propose EBIO, an efficient block I/O stack for NVMe SSD, to improve the overall performance of mixed workloads. EBIO contains an on-demand queue management strategy (ODQM) and a reusable I/O management strategy (RERM). Specifically, ODQM eliminates I/O wait by dynamically adding queues for I/O-intensive workloads and leverages I/O generation time to guarantee strong sequential consistency and fairness in scheduling I/O requests. RERM reduces the overhead caused by repeatedly allocating I/O request objects for I/O-intensive workloads by reusing the allocated objects. Experimental results show that, compared to the state-of-the-art approaches, EBIO improves IOPS by up to 16.44% and reduces I/O latency by up to 32.76%. |
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ISSN: | 0278-0070 1937-4151 |
DOI: | 10.1109/TCAD.2023.3296369 |