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arXiv:2610.39017 · v1

DistOptimize: Automatic Optimization of Distributed Protocols

首次提交 2026-10-29 06:45
版本更新 2026-10-29 06:45
雷达观测 2026-10-30 11:25
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摘要

Distributed consensus and consistency protocols are difficult to reason about yet foundational to the cloud; as such, they often undergo a rigorous proof and formal verification process before deployment. The same level of rigor is rarely applied to protocol modifications, which occur frequently in production and threaten to compromise safety. In this paper, we eliminate the risk of safety violations from manual modifications by presenting an automatic optimizer for distributed protocols: DistOptimize. DistOptimize adapts throughput optimizations from academic languages to frameworks used in production, verifying the correctness of the rewrites in Rocq and automating their application through a combination of calibration and ILP-based search space navigation. Applied to both fundamental distributed protocols and protocols used at AWS, DistOptimize improves throughput by up to 4x and increases latency by at most 0.3ms.

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v1 · 2026-10-29 06:45 · 最新观测版本

DistOptimize: Automatic Optimization of Distributed Protocols

Distributed consensus and consistency protocols are difficult to reason about yet foundational to the cloud; as such, they often undergo a rigorous proof and formal verification process before deployment. The same level of rigor is rarely applied to protocol modifications, which occur frequently in production and threaten to compromise safety. In this paper, we eliminate the risk of safety violations from manual modifications by presenting an automatic optimizer for distributed protocols: DistOptimize. DistOptimize adapts throughput optimizations from academic languages to frameworks used in production, verifying the correctness of the rewrites in Rocq and automating their application through a combination of calibration and ILP-based search space navigation. Applied to both fundamental distributed protocols and protocols used at AWS, DistOptimize improves throughput by up to 4x and increases latency by at most 0.3ms.

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