Survey of Machine Learning for Software-assisted Hardware Design Verification: Past, Present, and Prospect
Nan Wu,
Yingjie Li,
Hang Yang
et al.
Abstract:With the ever-increasing hardware design complexity comes the realization that efforts required for hardware verification increase at an even faster rate. Driven by the push from the desired verification productivity boost and the pull from leap-ahead capabilities of machine learning (ML), recent years have witnessed the emergence of exploiting ML-based techniques to improve the efficiency of hardware verification. In this paper, we present a panoramic view of how ML-based techniques are embraced in hardware d… Show more
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