Optimizing I/O Operations in File Systems for Fast Storage Devices

• Published in: IEEE transactions on computers 2017-06, Vol.66 (6), p.1071-1084
• Main Authors: Son, Yongseok, Yeom, Heon Young, Han, Hyuck
• Format: Article
• Language: English
• Subjects: Cloud computing; Computer storage devices; Computers; Data recovery; File system; Hardware reviews; I/O stack; journaling; Linux; Memory devices; Memory management; non-volatile memory; Nonvolatile memory; Optimization; Performance evaluation; Phase transitions; Servers; Software; Storage area networks; Storage systems
• ISSN: 0018-9340; 1557-9956
• DOI: 10.1109/TC.2016.2635644

Fast non-volatile memory (NVM) technologies (e.g., phase change memory, spin-transfer torque memory, and MRAM) provide high performance to legacy storage systems. These NVM technologies have attractive features, such as low latency and high throughput to satisfy application performance. Accordingly, fast storage devices based on fast NVM lead to a rapid increase in the demand for diverse computer systems and environments (e.g., cloud platforms, web servers, and database systems) where they are expected to be used as primary storage. Despite the promised benefits provided by fast storage devices, modern file systems do not take advantage of the storage's full performance. In this article, we analyze and explore existing I/O strategies in read, write, journal I/ O, and recovery paths between the file system and the storage device. The analysis shows that existing I/O strategies are an obstacle to get maximum performance of fast storage devices. To address this issue, we propose efficient I/O strategies that enable file systems to fully exploit the performance of fast storage devices. Our main idea is to transfer requests from discontiguous host memory buffers in the file systems to discontiguous storage segments in one I/O request to get maximize I/O performance. We implemented our scheme to read, write, journal I/O and recovery operations in the EXT4 file system and the JBD2 module. We demonstrate the implication of our idea in terms of application performance through well-known benchmarks. The experimental results show that our optimized file system achieves better performance than the existing file system, with improvements of up to 1.54 ×, 1.96×, and 2.28× on ordered mode, data journaling mode, and recovery, respectively.