Guaranteed Yet Hard to Find: Uncovering FPGA Routing Convergence Paradox

Abstract Routing is one of the major challenges of FPGA compilation. PathFinder is a ubiquitous FPGA routing algorithm used in industry and academia due to its ability to adapt to arbitrary routing architectures and user circuits. However, to this day, we do not fully understand why PathFinder works so well and what its limitations are. When a circuit fails to route, it is difficult to pinpoint the problem: architecture or algorithm. Usually, in such cases, either Pathfinder is fine-tuned or routing resources are added to the architecture to improve routability, thereby ignoring the inherent inefficiencies that may exist in Pathfinder, which further prevents us from designing silicon-efficient architectures. In this work, to pinpoint the problem, we construct constrained routing problems where nets have access to limited but specific routing resources that guarantee a legal routing solution. Yet, even with a state-of-the-art implementation, PathFinder fails to find the guaranteed routing solution or any other solution, highlighting issues specific to PathFinder. The reduced search space makes the underlying behavior more accessible for analysis and reasoning, allowing us to identify inefficiencies in the current PathFinder paradigm and propose a solution to address them. We uncovered that PathFinder’s greedy approach of routing individual connections yields an inefficient route tree, in terms of the total number of nodes. We then transfer this insight—through a simple yet effective algorithm—from the constrained to the standard setting, where the search space is not reduced. By constructing more efficient route trees, the routed wirelength and the number of routed connections were reduced by 6.4% and 3.6%, respectively, on average.

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Recommended citation: Shashwat Shrivastava, Stefan Nikolić, Sun Tanaka, Chirag Ravishankar, Dinesh Gaitonde, and Mirjana Stojilović. "Guaranteed Yet Hard to Find: Uncovering FPGA Routing Convergence Paradox"In Proceedings of the 2025 IEEE 33rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 05 2025
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