Pipeline Automation Framework for Reusable High-throughput Network Applications on FPGA

2026-01-21

AI Summary

This work addresses the challenges posed by the lengthy and platform-specific nature of FPGA hardware design, which hinders flexible deployment in high-throughput, agile network infrastructures. To overcome this limitation, the authors propose PAF, a framework that employs a pipeline-oriented, parameterized architectural design methodology using the Chisel hardware construction language. By decoupling architectural intent from low-level implementation details, PAF enables fine-grained hardware control while substantially reducing code complexity. The framework facilitates efficient reuse and automated optimization of the same network application across diverse FPGA platforms. Experimental evaluation on an industrial-grade packet classification system demonstrates that PAF achieves performance and resource utilization comparable to hand-optimized designs, while significantly improving development productivity and portability.

Technology Category

• Machine Learning: Hardware-aware ML
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Mechanism Design

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In a context of ever-growing worldwide communication traffic, cloud service providers aim at deploying scalable infrastructures to address heterogeneous needs. Part of the network infrastructure, FPGAs are tailored to guarantee low-latency and high-throughput packet processing. However, slowness of the hardware design process impairs FPGA ability to be part of an agile infrastructure under constant evolution, from incident response to long-term transformation. Deploying and maintaining network functionalities across a wide variety of FPGAs raises the need to fine-tune hardware designs for several FPGA targets. To address this issue, we introduce PAF, an open-source architectural parameterization framework based on a pipeline-oriented design methodology. PAF (Pipeline Automation Framework) implementation is based on Chisel, a Scala-embedded Hardware Construction Language (HCL), that we leverage to interface with circuit elaboration. Applied to industrial network packet classification systems, PAF demonstrates efficient parameterization abilities, enabling to reuse and optimize the same pipelined design on several FPGAs. In addition, PAF focuses the pipeline description on the architectural intent, incidentally reducing the number of lines of code to express complex functionalities. Finally, PAF confirms that automation does not imply any loss of tight control on the architecture by achieving on par performance and resource usage with equivalent exhaustively described implementations.

Problem

• FPGA
• pipeline automation
• high-throughput networking
• hardware design reuse
• network infrastructure agility

Innovation

• FPGA
• pipeline automation
• hardware parameterization
• Chisel
• high-throughput networking