Waverunner: An Elegant Approach to Hardware Acceleration of State Machine Replication
Mohammadreza Alimadadi, Hieu Mai, Shenghsun Cho, Michael Ferdman, Peter A. Milder, Shuai Mu
摘要
State machine replication (SMR) is a core mechanism for building highly available and consistent systems. In this paper, we propose Waverunner, a new approach to accelerate SMR using FPGA-based SmartNICs. Our approach does not implement the entire SMR system in hardware; instead, it is a hybrid software/hardware system. We make the observation that, despite the complexity of SMR, the most common routine-the data replication-is actually simple. The complex parts (leader election, failure recovery, etc.) are rarely used in modern datacenters where failures are only occasional. These complex routines are not performance critical; their software implementations are fast enough and do not need acceleration. Therefore, our system uses FPGA assistance to accelerate data replication, and leaves the rest to the traditional software implementation of SMR.
Our Waverunner approach is beneficial in both the common and the rare case situations. In the common case, the system runs at the speed of the network, with a 99th percentile latency of 1.8 µs achieved without batching on minimum-size packets at network line rate (85.5 Gbps in our evaluation). In rare cases, to handle uncommon situations such as leader failure and failure recovery, the system uses traditional software to guarantee correctness, which is much easier to develop and maintain than hardware-based implementations. Overall, our experience confirms Waverunner as an effective and practical solution for hardware accelerated SMR-achieving most of the benefits of hardware acceleration with minimum added complexity and implementation effort.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper3
- DINT: Fast In-Kernel Distributed Transactions with eBPFYang Zhou, Xingyu Xiang, Matthew Kiley, Sowmya Dharanipragada 等NSDI 2024 · 被引用 40 次
- ACCL+: an FPGA-Based Collective Engine for Distributed ApplicationsZhenhao He, Dario Korolija, Yu Zhu, Benjamin Ramhorst 等OSDI 2024 · 被引用 12 次
- FiDe: Reliable and Fast Crash Failure Detection to Boost Datacenter CoordinationDavide Rovelli, Pavel Chuprikov, Philipp Berdesinski, Ali Pahlevan 等USENIX ATC 2025 · 被引用 2 次
它引用的顶会 Paper18
- Understanding host network stack overheadsQizhe Cai, Shubham Chaudhary, Midhul Vuppalapati, Jaehyun Hwang 等SIGCOMM 2021 · 被引用 150 次
- PANIC: A High-Performance Programmable NIC for Multi-tenant NetworksJiaxin Lin, Kiran Patel, Brent E. Stephens, Anirudh Sivaraman 等OSDI 2020 · 被引用 104 次
- The Demikernel Datapath OS Architecture for Microsecond-scale Datacenter SystemsIrene Zhang, Amanda Raybuck, Pratyush Patel, Kirk Olynyk 等SOSP 2021 · 被引用 83 次
- BMC: Accelerating Memcached using Safe In-kernel Caching and Pre-stack ProcessingYoann Ghigoff, Julien Sopena, Kahina Lazri, Antoine Blin 等NSDI 2021 · 被引用 79 次
- The nanoPU: A Nanosecond Network Stack for DatacentersStephen Ibanez, Alex Mallery, Serhat Arslan, Theo Jepsen 等OSDI 2021 · 被引用 74 次
相关 Paper
- Rabia: Simplifying State-Machine Replication Through RandomizationHaochen Pan, Jesse Tuglu, Neo Zhou, Tianshu Wang 等SOSP 2021 · 被引用 20 次
- Abraxas: Throughput-Efficient Hybrid Asynchronous ConsensusErica Blum, Jonathan Katz, Julian Loss, Kartik Nayak 等CCS 2023 · 被引用 11 次
- Microsecond Consensus for Microsecond ApplicationsMarcos K. Aguilera, Naama Ben-David, Rachid Guerraoui, Virendra J. Marathe 等OSDI 2020 · 被引用 73 次
- RpcNIC: Enabling Efficient Datacenter RPC Offloading on PCIe-attached SmartNICsJie Zhang, Hongjing Huang, Xuzheng Chen, Xiang Li 等HPCA 2025 · 被引用 6 次
- SmartNIC-Enabled Live Migration for Storage-Optimized VMs with PYROCUMULUSJiechen Zhao, Ran Shu, Lei Qu, Ziyue Yang 等NSDI 2026
