Yang Zhou, Harvard University; Hassan M. G. Wassel, Google; Sihang Liu, University of Virginia; Jiaqi Gao and James Mickens, Harvard University; Minlan Yu, Harvard University and Google; Chris Kennelly, Paul Turner, and David E. Culler, Google; Henry M. Levy, University of Washington and Google; Amin Vahdat, Google
Far memory systems allow an application to transparently access local memory as well as memory belonging to remote machines. Fault tolerance is a critical property of any practical approach for far memory, since machine failures (both planned and unplanned) are endemic in datacenters. However, designing a fault tolerance scheme that is efficient with respect to both computation and storage is difficult. In this paper, we introduce Carbink, a far memory system that uses erasure-coding, remote memory compaction, one-sided RMAs, and offloadable parity calculations to achieve fast, storage-efficient fault tolerance. Compared to Hydra, a state-of-the-art fault-tolerant system for far memory, Carbink has 29% lower tail latency and 48% higher application performance, with at most 35% higher memory usage.
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author = {Yang Zhou and Hassan M. G. Wassel and Sihang Liu and Jiaqi Gao and James Mickens and Minlan Yu and Chris Kennelly and Paul Turner and David E. Culler and Henry M. Levy and Amin Vahdat},
title = {Carbink: {Fault-Tolerant} Far Memory},
booktitle = {16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)},
year = {2022},
isbn = {978-1-939133-28-1},
address = {Carlsbad, CA},
pages = {55--71},
url = {https://www.usenix.org/conference/osdi22/presentation/zhou-yang},
publisher = {USENIX Association},
month = jul
}