计算机科学
字节
并行计算
吞吐量
寻呼
移液管
网络数据包
符号
计算机硬件
操作系统
算术
数学
计算机网络
化学
无线
物理化学
作者
Shuhan Bai,Hu Wan,Yun Huang,Xuan Sun,Fei Wu,Changsheng Xie,Hung‐Sheng Hsieh,Tei‐Wei Kuo,Chun Jason Xue
标识
DOI:10.1109/tcad.2023.3276520
摘要
Big data applications, such as recommendation system and social network, often generate a huge number of fine-grained reads to the storage. Block-oriented storage devices upon the traditional storage system rely on the paging mechanism to migrate pages to the host DRAM, tending to suffer from these fine-grained read operations in terms of I/O traffic as well as performance. Motivated by this challenge, an efficient fine-grained read framework, Pipette, is proposed in this article as an extension to the traditional I/O framework. With adaptive design for caching, merging, and scheduling, Pipette explores locality and acceleration for fine-grained read requests to establish an efficient byte-granular read path upon the dedicated byte-addressable interface. When the Pipette prototype on an SSD runs popular workloads, we measured throughput gains by up to 50% and 54% with traffic reduction in the range of $41.3\times $ and $56.5\times $ .
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