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A refinement relation captures the state equivalence between two sequential circuits. It finds applications in various tasks of VLSI design automation, including regression verification, behavioral model synthesis, assertion synthesis, and design space exploration. However, manually constructing a refinement relation requires an engineer to have both domain knowledge and expertise in formal methods, which is especially challenging for complex designs after significant transformations. This paper presents a rigorous and efficient sequential equivalence checking algorithm for non-cycle-accurate designs. The algorithm can automatically find a concise and human-comprehensible refinement relation between two designs, helping engineers understand the essence of design transformations. We demonstrate the usefulness and efficiency of the proposed algorithm with experiments and case studies. In particular, we showcase how refinement relations can facilitate error detection and correction for LLM-generated RTL designs.
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SE3: Sequential Equivalence Checking for Non-Cycle-Accurate Design Transformations
In high-level design explorations, many useful optimizations transform a circuit into another with different operating cycles for a better trade-off between performance and resource usage. How to efficiently check their equivalence is critical and challenging since most existing equivalence checkers are designed for cycle-accurate circuits. This paper presents SE3, an efficient sequential equivalence checker without assumption on cycle-accuracy, latch mapping, or I/O interface of the checked circuits. It proves the equivalence of two circuits by computing an equivalence relation between the states of the two circuits and utilizes syntax abstraction to accelerate this process. Experimental results show that SE3 is significantly faster than state-of-the-art sequential equivalence checking algorithms.
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- PAR ID:
- 10412505
- Date Published:
- Journal Name:
- Proceedings ACM IEEE Design Automation Conference
- ISSN:
- 0738-100X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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