An Equivalence Checking Framework for Agile Hardware Design

Agile hardware design enables designers to produce new design iterations efficiently. Equivalence checking is critical in ensuring that a new design iteration conforms to its speci-fication. In this paper, we introduce an equivalence checking framework for hardware designs represented in HalideIR. HalideIR is a popular intermediate representation in soft-ware domains such as deep learning and image processing, and it is increasingly utilized in agile hardware design. We have developed a fully automatic equivalence checking work-flow seamlessly integrated with HalideIR and several opti-mizations that leverage the incremental nature of agile hard-ware design to scale equivalence checking. Evaluations of two deep learning accelerator designs show our automatic equivalence checking framework scales to hardware designs of practical sizes and detects inconsistencies that manually crafted tests have missed.