@inproceedings{a7a2ab9d70db4b2e95cd22da07909ea7,
title = "Efficiency of Buffer Caching in Computing-Intensive Workloads",
abstract = "With the recent advent of the fourth industrial revolution, computing-intensive workloads such as big data and machine learning emerge every day. Even though the workloads are computation-intensive, there are file I/Os to access storage, and we need to improve the I/O performance by using buffer caching. This paper analyzes the efficiency of the buffer caching in the emerging computing-intensive workloads, and observes some peculiar I/O patterns, which degrades the performance of the buffer caching significantly. To relieve this problem, we present a new buffer caching scheme for improving the I/O performance of computing-intensive workloads. Simulation experiments with real-world traces show that the proposed buffer caching scheme improves the cache miss rate against the well-known LRU buffer caching policy by 35.2% on average and up to 81.6%.",
keywords = "LRU, buffer caching, computing-intensive workload, file I/O, storage",
author = "Hyokyung Bahn",
note = "Funding Information: ACKNOWLEDGMENT This work was supported by the ICT R&D program of MSIP/IITP (2018-0-00549, Extremely scalable order preserving OS for manycore and non-volatile memory) and also by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2019R1A2C1009275). Publisher Copyright: {\textcopyright} 2020 IEEE.; null ; Conference date: 18-12-2020 Through 20-12-2020",
year = "2020",
month = dec,
doi = "10.1109/ICISCE50968.2020.00120",
language = "English",
series = "Proceedings - 2020 7th International Conference on Information Science and Control Engineering, ICISCE 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "548--552",
editor = "Shaozi Li and Ying Dai and Jianwei Ma and Yun Cheng",
booktitle = "Proceedings - 2020 7th International Conference on Information Science and Control Engineering, ICISCE 2020",
}