TriCache: A User-Transparent Block Cache Enabling High-Performance Out-of-Core Processing with In-Memory Programs


Guanyu Feng and Huanqi Cao, Tsinghua University; Xiaowei Zhu, Ant Group; Bowen Yu, Yuanwei Wang, Zixuan Ma, Shengqi Chen, and Wenguang Chen, Tsinghua University


Out-of-core systems rely on high-performance cache sub-systems to reduce the number of I/O operations. While the page cache in modern operating systems enables transparent access to memory and storage devices, it suffers from efficiency and scalability issues on cache misses, forcing out-of-core systems to design and implement their own cache components, which is a non-trivial task.

This study proposes TriCache, a cache mechanism that enables in-memory programs to efficiently process out-of-core datasets without requiring any code rewrite. It provides a virtual memory interface on top of the conventional block interface to simultaneously achieve user transparency and sufficient out-of-core performance. A multi-level block cache design is proposed to address the challenge of per-access address translations required by a memory interface. It can exploit spatial and temporal localities in memory or storage accesses to render storage-to-memory address translation and page-level concurrency control adequately efficient for the virtual-memory interface.

Our evaluation shows that in-memory systems operating on top of TriCache can outperform Linux OS page cache by more than one order of magnitude, and can deliver performance comparable to or even better than that of corresponding counterparts designed specifically for out-of-core scenarios.

OSDI '22 Open Access Sponsored by NetApp

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@inproceedings {280858,
author = {Guanyu Feng and Huanqi Cao and Xiaowei Zhu and Bowen Yu and Yuanwei Wang and Zixuan Ma and Shengqi Chen and Wenguang Chen},
title = {{TriCache}: A {User-Transparent} Block Cache Enabling {High-Performance} {Out-of-Core} Processing with {In-Memory} Programs},
booktitle = {16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)},
year = {2022},
isbn = {978-1-939133-28-1},
address = {Carlsbad, CA},
pages = {395--411},
url = {},
publisher = {USENIX Association},
month = jul

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