From the 1 of 7 linked papers with an AI index.
7 papers
NeuroAbs: A Neuro-Symbolic RTL Abstraction Framework for Property Checking Acceleration
Zhiyuan Yan, Xiaofeng Zhou, Ziyue Zheng +5
Formal verification is a crucial technique for ensuring the functional correctness of hardware designs. In the context of property checking, a key challenge is how to efficiently p…
A-IC3: Learning-Guided Adaptive Inductive Generalization for Hardware Model Checking
Xiaofeng Zhou, Guangyu Hu, Hongce Zhang +1
The paper introduces a lightweight machine‑learning framework that uses a multi‑armed bandit to dynamically select inductive generalization strategies within the IC3 hardware model…
AutoINV: Automated Invariant Generation Framework for Formal Verification on High-Level Synthesis Designs
Xiaofeng Zhou, Linfeng Du, Guangyu Hu +3
High-level synthesis (HLS) transforms an algorithmic description of hardware from a higher abstraction (e.g., C/C++) into a register-transfer level (RTL) design, offering reduced d…
AutoPDR: Circuit-Aware Solver Configuration Prediction for Hardware Model Checking
Guangyu Hu, Chen Chen, Xiaofeng Zhou +3
Property Directed Reachability (PDR) is a powerful algorithm for formal verification of hardware and software systems, but its performance is highly sensitive to parameter configur…
LeGend: A Data-Driven Framework for Lemma Generation in Hardware Model Checking
Mingkai Miao, Guangyu Hu, Wei Zhang +1
Property checking of RTL designs is a central task in formal verification. Among available engines, IC3/PDR is a widely used backbone whose performance critically depends on induct…
EvolveGen: Algorithmic Level Hardware Model Checking Benchmark Generation through Reinforcement Learning
Guangyu Hu, Xiaofeng Zhou, Wei Zhang +1
Progress in hardware model checking depends critically on high-quality benchmarks. However, the community faces a significant benchmark gap: existing suites are limited in number,…