Intra-request Lag-aware Cache Management to Enhance I/O Responsiveness of SSDs

Solid State Disks (SSDs) provide high degrees of channel-level parallelism, and sub-requests of a large request are forwarded to different flash channels to maximize parallelism and utilization. The scheduler, however, may experience differential wait times since their individual queues of channels are not coordinated and keep balanced workloads at all times. Since a large request is regarded as a complete only when its last sub-request is completed, some of its sub-requests that are completed earlier inevitably wait for this last one that is termed as intra-request lag , thus affecting I/O responsiveness. This article proposes intra-request lag-aware cache management to maximize channel-level read parallelism, thus improving user experience, as well as balance I/O workloads over all SSD channels. Once a part of sub-request(s) belonging to the same large read requests are blocked on the congested channel(s), indicating intra-request lag(s) appear, we preferentially load the lag-corresponding data, instead of all relevant data of read request, into the data cache. Consequently, it can respond quickly and balance the workload over channels if the read is hit in the near future. Besides, in order to specifically buffer the data of small read requests or the data of intra-request lags of large read request to improve read responsiveness, we present a cache partition model for splitting the data cache into the read cache and the write cache. Trace-driven experiments show that our proposal can reduce the long-tail latency of I/O requests by 26.2 % at the 99.9-th percentile, and the overall I/O time by 35.0 % on average, in contrast to existing approaches.