Skip to content

Author

Aman Arora

1 paper indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Jul 2026

VPR-Evolve: Multi-Agent-Driven Algorithm Evolution for FPGA Place and Route

CAD tools typically apply the same fixed, hand-designed algorithms across circuits with widely different structural and timing characteristics. A common way to specialize these one-size-fits-all flows to a target design is to tune the CAD tool's hyperparameters. However, hyperparameter tuning can only select among behaviors already implemented by the fixed algorithm, limiting the achievable quality of results while requiring many expensive place-and-route evaluations. We present VPR-Evolve, a multi-agent framework that specializes Versatile Place and Route (VPR), the open-source FPGA pack-place-and-route engine in the Verilog-to-Routing (VTR) flow, by evolving its source code for each design. VPR-Evolve uses LLM agents to propose, implement, and evaluate code-level modifications, while a shared memory records prior outcomes and guides subsequent evolution. Every candidate is evaluated through a complete VPR build and run, directly optimizing a composite score measured as a weighted function of critical-path delay (CPD), routed wirelength (WL), and tool runtime (RT). Across five VTR-9 benchmark circuits, VPR-Evolve improves the composite score by up to 2.7% over stock VPR in VTR-9. Relative to stock VPR, it reduces CPD by up to 9.8%, routed WL by up to 18.1%, and tool RT by up to 79.3%. VPR-Evolve reduces CPD by up to 6.0%, routed WL by up to 2.2%, and tool RT by up to 7.8% compared with a hyperparameter-tuning baseline.

Qi-Hang Wu, Taizun Jafri, Aman Arora et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.