Bai, ShuhanShuhanBaiWan, HuHuWanHuang, YunYunHuangSun, XuanXuanSunWu, FeiFeiWuXie, ChangshengChangshengXieHsieh, Hung ChihHung ChihHsiehTEI-WEI KUOXue, Chun JasonChun JasonXue2023-06-152023-06-152022-07-1097814503914290738100Xhttps://scholars.lib.ntu.edu.tw/handle/123456789/632696Big 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 tend to suffer from these fine-grained read operations in terms of I/O traffic as well as performance. Motivated by this challenge, a fine-grained read framework, Pipette, is proposed in this paper, as an extension to the traditional I/O framework. With an adaptive caching design, Pipette framework offers a tremendous reduction in I/O traffic as well as achieves significant performance gain. A Pipette prototype was implemented with Ext4 file system on an SSD for two real-world applications, where the I/O throughput is improved by 31.6% and 33.5%, and the I/O traffic is reduced by 95.6% and 93.6%, respectively.file system | fine-grained reads | solid-state drive[SDGs]SDG11conference paper10.1145/3489517.35304672-s2.0-85137473067https://api.elsevier.com/content/abstract/scopus_id/85137473067