2018 International Conference On Computer Aided Design

The Premier Conference Devoted to Technical Innovations in Electronic Design Automation

November 5-8, 2018Hilton San Diego Resort & Spa San Diego, CA

MP Associates, Inc.

THURSDAY November 08, 8:30am - 4:00pm | Riviera

International Workshop on Design Automation for Analog and Mixed-Signal Circuit

Sheriff Sadiqbatcha - Univ. of California, Riverside
David Pan - Univ. of Texas at Austin
Mike Chen - Univ. of Southern California
Peng Li - Texas A&M Univ.
Eric Keiter - Sandia National Laboratories
Zheng Zang - Univ. of California, Santa Barbara
Xiang Chen - George Mason Univ.
Keith Bowman - Qualcomm Technologies, Inc.
Mingoo Seok - Columbia Univ.
Subhanshu Gupta - Washington State Univ.
Jie Gu - Northwestern Univ.
Zhuo Feng - Michigan Technological Univ.
Xin Li - Duke Univ.
Jaeha Kim - Seoul National Univ.
Mark Po-Hung Lin - National Chung Cheng Univ.
Xuan Zeng - Fudan Univ.

A substantial portion of modern integrated circuits are analog and mixed-signal (AMS) circuits that provide critical functionality such as signal conversion. Over the past several decades, aggressive scaling of IC technologies, and the integration of heterogeneous physical domains on a chip, substantially complicates the design of AMS circuits. On the one hand, their modeling and design becomes extremely complex. On the other hand, their interplay with the rest of the system-on-chip challenges design, verification and test. The new technology trends bring enormous challenges and opportunities for AMS design automation. This is reflected by an increase in research activity on AMS CAD worldwide. Many emerging application brings tremendous new interest in developing analog mixed-signal circuits that accelerate the computing task. Examples include energy efficient neuromorphic computing based analog neurons or memristor devices, time or spiking based circuits for machine learning implementation, resonant based computing or PCM circuits, etc. We will feature this type of new emerging computing methodology in this year’s workshop. The purpose of this workshop is to bring together academic and industrial researchers from both design and CAD communities to report recent advances and motivate new research topics and directions in this area. Special focuses will be given to the emerging non-traditional analog mixed-signal computing methodology for machine learning, neuromorphic computing.