Improving the SSD Performance by Exploiting Request Characteristics and Internal Parallelism

Improving the SSD Performance by Exploiting Request Characteristics and Internal Parallelism
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利用请求特征和内部并行性提高SSD性能

DOI:
10.1109/tcad.2017.2697961
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发表时间:
2018-02
期刊:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (CCF A类期刊)
影响因子:
--
通讯作者:
Lide Duan
Lide Duan
中科院分区:
其他
文献类型:
--
作者:
Bo Mao;Suzhen Wu;Lide Duan

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随着数据量的爆炸式增长,I/O瓶颈已成为大数据分析的一个日益严峻的挑战。在存储系统中引入高性能的基于闪存的固态硬盘(SSD)是非常迫切和重要的。然而,由于现有系统主要是为传统的磁性硬盘驱动器设计的,因此在现有系统中直接结合SSD不能充分利用SSD的性能优势。在本文中,我们提出了一种新的I/O SSD调度器,即两栖,利用高层次的请求特性和低层次的并行闪存芯片,以提高基于SSD的存储系统的性能。Amphibian包括两种性能增强方案:1)基于大小的请求排序,在处理中优先处理大小较小的请求; 2)垃圾收集(GC)感知请求调度,延迟向处于GC状态的闪存芯片发出请求。Amphibian中采用的这两种方案显著减少了来自主机的请求的平均等待时间。我们对三种类型的SSD进行的广泛评估结果表明,与现有的I/O存储器相比,Amphibian大大提高了基于SSD的存储系统的吞吐量和平均响应时间,从而提高了系统的I/O性能。
With the explosive growth in the data volume, the I/O bottleneck has become an increasingly daunting challenge for big data analytics. It is urgent and important to introduce high-performance flash-based solid state drives (SSDs) into the storage systems. However, since the existing systems are primarily designed for conventional magnetic hard disk drives, directly incorporating SSDs in the existing systems cannot fully exploit SSDs’ performance advantages. In this paper, we propose a new I/O scheduler for SSDs, namely Amphibian, that exploits the high-level request characteristics and low-level parallelism of flash chips to improve the performance of SSD-based storage systems. Amphibian includes two performance enhancement schemes: 1) size-based request ordering, which prioritizes requests with small sizes in processing and 2) garbage collection (GC)-aware request dispatching that delays issuing requests to flash chips that are in the GC state. These two schemes employed in Amphibian significantly reduce the average waiting times of the requests from the host. Our extensive evaluation results derived from three types of SSDs show that, compared with the existing I/O schedulers, Amphibian greatly improves both throughput and average response times for SSD-based storage systems, thus improving the I/O performance of the systems.
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