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Emerging Multicore SoC SmartNICs, enclosing rich computing resources (e.g., a multicore processor, onboard DRAM, accelerators, programmable DMA engines), hold the potential to offload generic datacenter server tasks. However, it is unclear how to use a SmartNIC efficiently and maximize the offloading benefits, especially for distributed applications. Towards this end, we characterize four commodity SmartNICs and summarize the offloading performance implications from four perspectives: traffic control, computing capability, onboard memory, and host communication. Based on our characterization, we build iPipe, an actor-based framework for offloading distributed applications onto SmartNICs. At the core of iPipe is a hybrid scheduler, combining FCFS and DRR-based processor sharing, which can tolerate tasks with variable execution costs and maximize NIC compute utilization. Using iPipe, we build a real-time data analytics engine, a distributed transaction system, and a replicated key-value store, and evaluate them on commodity SmartNICs. Our evaluations show that when processing 10/25Gbps of application bandwidth, NIC-side offloading can save up to 3.1/2.2 beefy Intel cores and lower application latencies by 23.0/28.0 μs. 

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.