Stow: A spatially and temporally optimized write caching algorithm

Abstract

Non-volatile write-back caches enable storage controllers to provide quick write response times by hiding the latency of the disks. Managing a write cache well is critical to the performance of storage controllers. Over two decades, various algorithms have been proposed, including the most popular, LRW, CSCAN, and WOW. While LRW leverages temporal locality in the workload, and CSCAN creates spatial locality in the destages, WOW combines the benefits of both temporal and spatial localities in a unified ordering for destages. However, there remains an equally important aspect of write caching to be considered, namely, the rate of destages. For the best performance, it is important to destage at a steady rate while making sure that the write cache is not under-utilized or over-committed. Most algorithms have not seriously considered this problem, and as a consequence, forgo a significant portion of the performance gains that can be achieved. We propose a simple and adaptive algorithm, STOW, which not only exploits both spatial and temporal localities in a new order of destages, but also facilitates and controls the rate of destages effectively. Further, STOW partitions the write cache into a sequential queue and a random queue, and dynamically and continuously adapts their relative sizes. Treating the two kinds of writes separately provides for better destage rate control, resistance to one-time sequential requests polluting the cache, and a workload-responsive write caching policy. STOW represents a leap ahead of all previously proposed write cache management algorithms. As anecdotal evidence, with a write cache of 32K pages, serving a 4+P RAID-5 array, using an SPC-1 Like Benchmark, STOW outperforms WOW by 70%, CSCAN by 96%, and LRW by 39%, in terms of measured throughput. STOW consistently provides much higher throughputs coupled with lower response times across a wide range of cache sizes, workloads, and experimental configurations.