With network requirements diverging across emerging applications, latency-critical services demand minimal logic delay, while hyperscale training and collectives require sustained line-rate throughput for synchronized bulk transfers. This divergence creates an urgent need for custom network switches tailored to specialized protocols and application-specific traffic patterns. This paper presents SPAC (Switch and Protocol Adaptive Customization), a novel approach that automates the generation of FPGA-based network switches co-optimized for custom protocols and application-specific traffic patterns. SPAC introduces a unified workflow with a domain-specific language (DSL) for protocol-architecture co-design, a library of modular HLS-based adaptive switch components, and a trace-aware Design Space Exploration (DSE) engine. By providing a multi-fidelity simulation stack, SPAC enables rapid identification of Pareto-optimal designs prior to deployment. We demonstrate the efficacy of the domain-specific adaptation of SPAC across a spectrum of real-world scenarios, spanning from latency-sensitive sensor and HFT networks to hyperscale datacenter fabrics. Experimental results show that by tailoring the micro-architecture and protocol to the specific workload, SPAC-generated designs reduce LUT and BRAM usage by 55% and 53%, respectively. Compared to fixed-architecture counterparts, SPAC delivers latency reductions ranging from 7.8% to 38.4% across various tasks while maintaining adequate resource consumption and packet drop rate.

翻译：随着新兴应用对网络需求的差异化发展，延迟敏感型服务要求极低的逻辑时延，而超大规模训练与集合通信需要维持线速吞吐量以支持同步批量传输。这种分化催生了针对专用协议与应用特定流量模式的定制网络交换机的迫切需求。本文提出SPAC（交换机与协议自适应定制），一种通过协同优化自定义协议与应用特定流量模式，实现FPGA网络交换机自动化生成的新方法。SPAC引入统一工作流，包括：用于协议架构协同设计的领域特定语言（DSL）、基于HLS的自适应模块化交换机组件库，以及支持迹感知的设计空间探索（DSE）引擎。通过多保真度仿真栈，SPAC能够在部署前快速识别帕累托最优设计。我们通过一系列真实场景验证了SPAC领域自适应方法的有效性，涵盖从延迟敏感型传感器与高频交易网络到超大规模数据中心网络架构。实验结果表明，通过针对具体工作负载定制微架构与协议，SPAC生成的方案使LUT与BRAM使用量分别降低55%和53%。相较于固定架构方案，SPAC在各类任务中实现7.8%至38.4%的延迟削减，同时保持合理的资源消耗与丢包率。