Towards low-latency I/O services for mixed workloads using ultra-low latency SSDs

Low-latency I/O services are essential for latency-sensitive workloads when they co-run with throughput-oriented workloads in cloud data centers. Although advanced SSDs such as Intel Optane SSDs can offer ultra-low latency at the device layer, I/O interference among various workloads through the I/O stack can still significantly enlarge I/O latency. It is still an open problem to best utilize ultra-low latency SSDs in cloud computing environments.

In this paper, we analyze the entire I/O stack and reveal that I/O interference is mainly attributed to resource contention in the SSD device, transactions commit in the file system, and costly process scheduling. To address these problems, we propose FastResponse, a holistic approach to use ultra-low latency SSDs for latency-sensitive workloads. First, we propose a new I/O scheduler at the block layer to throttle I/O requests of throughput-oriented workloads, and thus reduce the resource contention in the SSD device. Second, we develop a fine-grained journaling scheme to reduce the latency of transaction at the file system layer. Third, we redesign Completely Fair Scheduler (CFS) to promote the priority of latency-sensitive processes. We implement FastResponse in Linux kernel and evaluate it with several mixed workloads. Compared with the vanilla Linux and the state-of-the-art SelectISR, FastResponse can reduce the average response time of latency-sensitive workloads by 18--70% and 10--67%, respectively, and reduce the 99.9th percentile response time by 58--80% and 52--78%, respectively. Meanwhile, the performance degradation for throughput-oriented workloads is less than 6%.