Making Watson fast

  • Authors:
  • E. A. Epstein;M. I. Schor;B. S. Iyer;A. Lally;E. W. Brown;J. Cwiklik

  • Affiliations:
  • IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY;IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY;IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY;IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY;IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY;IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY

  • Venue:
  • IBM Journal of Research and Development
  • Year:
  • 2012

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Abstract

IBM Watson™ is a system created to demonstrate DeepQA technology by competing against human champions in a question-answering game designed for people. The DeepQA architecture was designed to be massively parallel, with an expectation that low latency response times could be achieved by doing parallel computation on many computers. This paper describes how a large set of deep natural-language processing programs were integrated into a single application, scaled out across thousands of central processing unit cores, and optimized to run fast enough to compete in live Jeopardy!™ games.