QZFS: QAT Accelerated Compression in File System for Application Agnostic and Cost Efficient Data Storage

Website Maintenance Alert

Due to scheduled maintenance on Wednesday, October 16, from 10:30 am to 4:30 pm Pacific Daylight Time (UTC -7), parts of the USENIX website (e.g., conference registration, user account changes) may not be available. We apologize for the inconvenience.

If you are trying to register for LISA19, please complete your registration before or after this time period.

Authors: 

Xiaokang Hu and Fuzong Wang, Shanghai Jiao Tong University, Intel Asia-Pacific R&D Ltd.; Weigang Li, Intel Asia-Pacific R&D Ltd.; Jian Li and Haibing Guan, Shanghai Jiao Tong University

Abstract: 

Data compression can not only provide space efficiency with lower Total Cost of Ownership (TCO) but also enhance I/O performance because of the reduced read/write operations. However, lossless compression algorithms with high compression ratio (e.g. gzip) inevitably incur high CPU resource consumption. Prior studies mainly leveraged general-purpose hardware accelerators such as GPU and FPGA to offload costly (de)compression operations for application workloads. This paper investigates ASIC-accelerated compression in file system to transparently benefit all applications running on it and provide high-performance and cost-efficient data storage. Based on IntelĀ® QAT ASIC, we propose QZFS that integrates QAT into ZFS file system to achieve efficient gzip (de)compression offloading at the file system layer. A compression service engine is introduced in QZFS to serve as an algorithm selector and implement compressibility-dependent offloading and selective offloading by source data size. More importantly, a QAT offloading module is designed to leverage the vectored I/O model to reconstruct data blocks, making them able to be used by QAT hardware without incurring extra memory copy. The comprehensive evaluation validates that QZFS can achieve up to 5x write throughput improvement for FIO micro-benchmark and more than 6x cost-efficiency enhancement for genomic data post-processing over the software-implemented alternative.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {234986,
author = {Xiaokang Hu and Fuzong Wang and Weigang Li and Jian Li and Haibing Guan},
title = {{QZFS}: {QAT} Accelerated Compression in File System for Application Agnostic and Cost Efficient Data Storage},
booktitle = {2019 {USENIX} Annual Technical Conference ({USENIX} {ATC} 19)},
year = {2019},
isbn = {978-1-939133-03-8},
address = {Renton, WA},
pages = {163--176},
url = {https://www.usenix.org/conference/atc19/presentation/hu-xiaokang},
publisher = {{USENIX} Association},
month = jul,
}

Presentation Video