XRP: In-Kernel Storage Functions with eBPF


Yuhong Zhong, Haoyu Li, Yu Jian Wu, Ioannis Zarkadas, Jeffrey Tao, Evan Mesterhazy, Michael Makris, and Junfeng Yang, Columbia University; Amy Tai, Google; Ryan Stutsman, University of Utah; Asaf Cidon, Columbia University

Awarded Best Paper!


With the emergence of microsecond-scale NVMe storage devices, the Linux kernel storage stack overhead has become significant, almost doubling access times. We present XRP, a framework that allows applications to execute user-defined storage functions, such as index lookups or aggregations, from an eBPF hook in the NVMe driver, safely bypassing most of the kernel’s storage stack. To preserve file system semantics, XRP propagates a small amount of kernel state to its NVMe driver hook where the user-registered eBPF functions are called. We show how two key-value stores, BPF-KV, a simple B+-tree key-value store, and WiredTiger, a popular log-structured merge tree storage engine, can leverage XRP to significantly improve throughput and latency.

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@inproceedings {280870,
author = {Yuhong Zhong and Haoyu Li and Yu Jian Wu and Ioannis Zarkadas and Jeffrey Tao and Evan Mesterhazy and Michael Makris and Junfeng Yang and Amy Tai and Ryan Stutsman and Asaf Cidon},
title = {{XRP}: {In-Kernel} Storage Functions with {eBPF}},
booktitle = {16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)},
year = {2022},
isbn = {978-1-939133-28-1},
address = {Carlsbad, CA},
pages = {375--393},
url = {https://www.usenix.org/conference/osdi22/presentation/zhong},
publisher = {USENIX Association},
month = jul

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