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Hydra : Resilient and Highly Available Remote Memory

Youngmoon Lee, Hasan Al Maruf, Mosharaf Chowdhury, Asaf Cidon, Kang G. Shin

2022Year
21Top-tier citations

Abstract

We present Hydra, a low-latency, low-overhead, and highly available resilience mechanism for remote memory. Hydra can access erasure-coded remote memory within a single-digit µs read/write latency, significantly improving the performance-efficiency tradeoff over the state-of-the-art -it performs similar to in-memory replication with 1.6× lower memory overhead. We also propose CodingSets, a novel coding group placement algorithm for erasure-coded data, that provides load balancing while reducing the probability of data loss under correlated failures by an order of magnitude. With Hydra, even when only 50% memory is local, unmodified memory-intensive applications achieve performance close to that of the fully in-memory case in the presence of remote failures and outperforms the state-of-the-art remote-memory solutions by up to 4.35×.

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