白皮書

A survey of machine learning applications in functional verification

photo of 3D stacked circuit board

Functional verification is computationally and data-intensive by nature, making it a natural target of machine learning applications. This paper provides a comprehensive and up-to-date analysis of FV problems addressable by ML.

Among the various ML techniques and algorithms, several emerging ones have demonstrated outstanding potential in FV. Yet despite the promising research results, critical challenges remain for applying ML in the industrial EDA environment. As well, the unavailability of high-quality verification data is impeding the research of ML in FV, so the authors call for further contributions to open verification datasets.

Share

相關資訊

Realize LIVE – Explore active reports in Active Workspace
Webinar

Realize LIVE – Explore active reports in Active Workspace

Watch this Realize LIVE on-demand session to learn how to build active reports in Teamcenter’s Active Workspace.

Achieve quality excellence with Teamcenter Quality
Webinar

Achieve quality excellence with Teamcenter Quality

Watch this Realize LIVE on-demand presentation session to stay updated on the latest developments and innovations in the Teamcenter Quality product line.

Meeting the requirements of the digital thread with simulation process and data management
Webinar

Meeting the requirements of the digital thread with simulation process and data management

Watch to learn how companies are realizing the value and benefits of the digital thread with simulation solutions for process and data management.