• DocumentCode
    3723348
  • Title

    Toward metrics of design automation research impact

  • Author

    Andrew B. Kahng;Mulong Luo;Gi-Joon Nam;Siddhartha Nath;David Z. Pan;Gabriel Robins

  • Author_Institution
    UC San Diego, CSE Dept., La Jolla, 92093, United States
  • fYear
    2015
  • Firstpage
    263
  • Lastpage
    270
  • Abstract
    Design automation (DA) research has for over fifty years been performed in academia, semiconductor and system companies, and EDA companies worldwide. This research has been enabling to continued scaling of design productivity and growth of the semiconductor industry. For product companies, funding program managers and individual researchers alike, a highly relevant question is: what DA research, and what DA research outcomes, ultimately have the greatest “impact”? In this paper, we present measurements and analyses of DA research outputs (papers, patents, EDA companies), upon which future metrics of DA research impact might be based. Our studies consider 47000+ conference and journal papers from 1964-2014; the inter-patent citation graph over 759000+ DA-related patents; abstracts of 1150+ U.S. NSF projects over a three-decade span; 36 research needs documents of the Semiconductor Research Corporation from 2000-2013; and market segmentation of hundreds of EDA companies. We identify several interesting correlations, but do not claim to identify causal relationships; indeed, connecting traditional measures of research output to real-world impacts seems quite challenging. We conclude with several directions and targets for future investigation.
  • Keywords
    "Patents","Companies","Conferences","Measurement","Design automation","Electronics industry"
  • Publisher
    ieee
  • Conference_Titel
    Computer-Aided Design (ICCAD), 2015 IEEE/ACM International Conference on
  • Type

    conf

  • DOI
    10.1109/ICCAD.2015.7372579
  • Filename
    7372579