TicTacBench: Benchmarking Timing Closure Capabilities of Coding Agents
Recent advances in large language models (LLMs) have led to the emergence of coding agents capable of performing complex engineering tasks, including register-transfer level (RTL) design and optimization. Existing RTL benchmarks mainly evaluate functional correctness and performance, power, and area (PPA) of the generated RTL designs, leaving agents' ability for \emph{timing closure} under-evaluated. We propose TicTacBench, a benchmark specifically designed to evaluate coding agents' capabilities for RTL-level timing closure under post-place-and-route (post-PnR) evaluation. TicTacBench contains 30 diverse tasks, each provided with a suboptimal RTL design, realistic timing constraints, fun...
| Authors | Bowei Wang, Zhigang Fang, Zhijie Yang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 20 September 2026 |
| Last updated at source | 20 September 2026 |
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