FORWORD: Accelerating Formal Datapath Verification via Word-Level Sweeping
Ziyi Yang, Guangyu Hu, Xiaofeng Zhou, Mingkai Miao, Changyuan Yu, Wei Zhang, Hongce Zhang

TL;DR
FORWORD is a novel word-level sweeping verification engine that enhances formal datapath verification by combining simulation and optimization, significantly outperforming existing bit-level and SMT-based methods.
Contribution
This paper introduces FORWORD, the first word-level sweeping engine for datapath verification, integrating simulation and adaptive optimization to improve efficiency and effectiveness.
Findings
Outperforms state-of-the-art bit-level SAT sweeping engines
Significantly outperforms monolithic SMT solving methods
Effectively identifies equivalent datapath pairs
Abstract
Modern circuit design process increasingly adopts high-level hardware construction languages and parameterized design methodologies to shorten development cycles and maintain high reusability, in contrast to traditional hardware description languages. Such designs often involve complex datapath with arithmetic operations, wide bit-vectors, and on-chip memories, whose scale and level of modeling often pose significant challenges to formal datapath verification. Traditional bit-level SAT sweeping techniques lack the necessary abstraction and adaptability that are required to establish equivalence at a higher level. In this paper, we propose FORWORD, a novel word-level sweeping verification engine tailored explicitly to formal datapath verification. FORWORD integrates randomized and constraint-driven word-level simulations, leveraging adaptive optimization to dynamically refine equivalent…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
