Authors:
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
Abstract:
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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From OSDI ‘22.