W07 Workshop on Machine Learning for CAD

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Jörg Henkel, Karlsruher Institut für Technologie (KIT), DE (Contact Jörg Henkel)
Hussam Amrouch, Karlsruhe Institute of Technology (KIT), DE (Contact Hussam Amrouch)
Marilyn Wolf, Georgia Tech, US (Contact Marilyn Wolf)

This workshop focuses on machine learning methods for all aspects of CAD and electronic system design. Advances in machine learning (ML) over the past half-dozen years have revolutionized the effectiveness of ML for a variety of applications. However, design processes present challenges that require parallel advances in ML and CAD as compared to traditional ML applications such as image classification. As such, the purpose of the workshop is to discuss, define and provide a roadmap for the special needs for ML for CAD where CAD is broadly defined as design time techniques as well as run-time techniques. The results of the workshop are planned for publication in form of a special issue at a major ACM or IEEE journal/magazine.

Topics of interest to this workshop include but are not limited to:

  • ML approaches to logic design.
  • Machine learning for physical design.
  • ML for analog design.
  • Machine learning methods to predict aging and reliability.
  • Labeled and unlabeled data in ML for CAD.
  • ML for power and thermal management.
  • ML techniques for resource management in manycores.

The workshop will include both submitted and invited speakers. Submissions should be sent by Friday, December 7 to wolf@ece.gatech.edu

Schedule and speakers to be announced.

For more information contact Marilyn Wolf wolf@ece.gatech.edu


07:30W07.1Registration Desk opens
08:30W07.2Workshops start
10:00W07.3Coffee break 1
12:00W07.4Lunch break
14:30W07.5Coffee break 2
17:30W07.6Workshops end