Synchronous Mirroring (SM) is a standard approach to building highly-available and fault-tolerant enterprise storage systems. SM ensures strong data consistency by maintaining multiple exact data replicas and synchronously propagating every update to all of them. Such strong consistency provides fault tolerance guarantees and a simple programming model coveted by enterprise system designers. For current storage devices, SM comes at modest performance overheads. This is because performing both local and remote updates simultaneously is only marginally slower than performing just local updates, due to the relatively slow performance of accesses to storage in todays systems. However, emerging persistent memory and ultra-low-latency network technologies necessitate a careful re-evaluation of the existing SM techniques, as these technologies present fundamentally different latency characteristics compared than their traditional counterparts. In addition to that, existing low-latency network technologies, such as Remote Direct Memory Access (RDMA), provide limited ordering guarantees and do not provide durability guarantees necessary for SM. To evaluate the performance implications of RDMA-based SM, we develop a rigorous testing framework that is based on emulated persistent memory. Our testing framework makes use of two different tools: (i) a configurable microbenchmark and (ii) a modified version of the WHISPER benchmark suite, which comprises a set of common cloud applications. Using this framework, we find that recently proposed RDMA primitives, such as remote commit, provide correctness guarantees, but do not take full advantage of the asynchronous nature of RDMA hardware. To this end, we propose new primitives enabling efficient and correct SM over RDMA, and use these primitives to develop two new techniques delivering high-performance SM of persistent memories.
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