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CalmWPC: A buffer management to calm down write performance cliff for NAND flash-based storage systems

机译:CalmWPC:一种缓冲区管理,可缓解基于NAND闪存的存储系统的写入性能下降

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NAND Flash-based solid state disks (i.e., SSDs) are widely applied in large-scale storage systems. However, NAND Flash is featured with the asymmetric read and write performance, high erase latency, and the limited number of program/erase cycles (P/Es). Under random write-intensive workloads, a garbage collection (i.e., GC) process inside SSDs causes write performance cliff, which causes high latency for I/O access and degrades SSD lifetime. In real-time transactional applications, such large write performance cliff affects the response time of I/O requests, thereby leading to serious critical errors in real-time applications.To handle this issue, we propose a buffer management strategy called CalmWPC to calm down SSD write performance cliff. CalmWPC seamlessly integrates a data cluster-based data management, a historical access-based prediction algorithm, a semantic fingerprint database. The prediction algorithm checks the future data-cluster activity while classifying the cluster based on its historical write operations. The fingerprint database stores semantic messages for write/update between the buffer and NAND Flash memory. With the fingerprint database in place, CalmWPC calculates the number of invalid data pages in a block in real time. CalmWPC flushes the data cluster into flash memory when the number of update pages reaches a predefined threshold. Our CalmWPC optimizes write performance cliff during GC under random-write workloads.Experimental results reveal that CalmWPC is able to reduce write performance cliff, improve the average latency of user I/Os, and optimize write amplification. Take Financial1 as an example, CalmWPC reduces the write performance cliff by averages of 60.9% and 60.0% compared with LRU and CFLRU. CalmWPC also shortens the response time of LRU and CFLRU by averages of 69.4% and 70.1%, respectively. (C) 2018 Elsevier B.V. All rights reserved.
机译:基于NAND闪存的固态盘(即,SSD)被广泛应用于大规模存储系统中。但是,NAND闪存具有非对称的读写性能,较高的擦除延迟以及有限的编程/擦除周期(P / E)。在随机的写入密集型工作负载下,SSD内的垃圾回收(即GC)进程会导致写入性能下降,从而导致I / O访问的高延迟并降低SSD的使用寿命。在实时事务应用程序中,如此大的写入性能悬崖会影响I / O请求的响应时间,从而导致实时应用程序中出现严重的严重错误。为解决此问题,我们提出了一种称为CalmWPC的缓冲区管理策略来使此问题平静下来。 SSD写入性能悬崖。 CalmWPC无缝集成了基于数据集群的数据管理,基于历史访问的预测算法和语义指纹数据库。预测算法会检查未来的数据集群活动,同时根据集群的历史写入操作对集群进行分类。指纹数据库存储用于在缓冲区和NAND闪存之间进行写/更新的语义消息。有了指纹数据库,CalmWPC可以实时计算一个块中无效数据页的数量。当更新页数达到预定义的阈值时,CalmWPC将数据群集刷新到闪存中。我们的CalmWPC优化了随机写入工作负载下GC期间的写入性能悬崖,实验结果表明CalmWPC能够降低写入性能悬崖,改善用户I / O的平均延迟并优化写入放大。以Financial1为例,与LRU和CFLRU相比,CalmWPC分别将写入性能下降了60.9%和60.0%。 CalmWPC还分别将LRU和CFLRU的响应时间平均缩短了69.4%和70.1%。 (C)2018 Elsevier B.V.保留所有权利。

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