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Agents · Code

Self-Evolving Logic Synthesis

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First page
Self-Evolving Logic Synthesis
The curator’s take

EDA tools like ABC have been hand-tuned by humans for decades. NVIDIA shows they can evolve themselves. This work introduces the first self-evolving logic synthesis framework, a multi-agent LLM system that autonomously refines the entire ABC codebase, generates and tests candidate optimization sequences against standard benchmark circuits, then merges improvements back into the base tool. No human engineer in the loop.

Key points
01

Multi-agent refinement of a real EDA toolchain: The framework assigns specialized agents to exploration, synthesis, and self-review tasks. Agents read and modify the ABC source directly, propose optimization flows, and run them against benchmark circuits such as EPFL, IWLS, and VTR, with three-pass human-domain knowledge injected through the pipeline.

02

Measured improvement over hand-tuned baselines: The evolved ABC variants produce better area, delay, and switching metrics than the hand-tuned reference on the benchmark suite, and the improvements persist under sensitivity analysis. This is a real gain on a tool the semiconductor industry depends on.

03

Codebase-level evolution, not just prompt tuning: The agents edit the ABC codebase itself, not just a configuration layer. That is a meaningful extension of the self-improving agent thread: the unit of improvement is real production code, not a prompt or policy.

04

Generalizable blueprint for domain tools: If agents can evolve a foundational semiconductor tool without manual engineering, the same pattern generalizes to any large, domain-specific codebase. It is a concrete extension of the self-improving agent thread, applied to infrastructure that shipping chips depend on.

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