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Our OSDI 2020 Paper “Assise: Performance and Availability via Client-local NVM in a Distributed File System”

At USENIX OSDI 2020, Waleed presented our paper titled “Assise: Performance and Availability via Client-local NVM in a Distributed File System”. The slides and video are available at the USENIX site. Alternatively, the PDF is available here, while video is available below:

This is joint work with researchers spread all over our planet: Thomas E. Anderson (University of Washington), Marco Canini (KAUST) Jongyul Kim (KAIST), Dejan Kostić (KTH Royal Institute of Technology), Youngjin Kwon (KAIST), Simon Peter (The University of Texas at Austin), Waleed Reda (KTH Royal Institute of Technology and Université catholique de Louvain), Henry N. Schuh (University of Washington), and Emmett Witchel (The University of Texas at Austin)

The full abstract is as follows:

The adoption of low latency persistent memory modules (PMMs) upends the long-established model of remote storage for distributed file systems. Instead, by colocating computation with PMM storage, we can provide applications with much higher IO performance, sub-second application failover, and strong consistency. To demonstrate this, we built the Assise distributed file system, based on a persistent, replicated coherence protocol that manages client-local PMM as a linearizable and crash-recoverable cache between applications and slower (and possibly remote) storage. Assise maximizes locality for all file IO by carrying out IO on process-local, socket-local, and client-local PMM whenever possible. Assise minimizes coherence overhead by maintaining consistency at IO operation granularity, rather than at fixed block sizes.

We compare Assise to Ceph/BlueStore, NFS, and Octopus on a cluster with Intel Optane DC PMMs and SSDs for common cloud applications and benchmarks, such as LevelDB, Postfix, and FileBench. We find that Assise improves write latency up to 22x, throughput up to 56x, fail-over time up to 103x, and scales up to 6x better than its counterparts, while providing stronger consistency semantics.