Still a fight to get it right: Verification in the era of machine learning

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We live in interesting times. Our systems have unprecedented levels of device integration. Analog and mixed signal components and devices form increasingly large parts of our designs built for low power and high flexibility. New architectures and models of computation that embrace variation like neuromorphic computing are a part of our horizon. Architectures specialized for neural networks and learning algorithms are being built as massive undertakings in contemporary industry as well as with hardware accelerators. Application specific hardware has seen a healthy resurgence for machine learning and vision applications. With all these innovations in architecture and design, how do we know if were getting them right? As designs get more complicated, the"price of the lunch" is paid by verification complexity. We have always aspired to build systems we dont know to check. That problem is going to get much more challenging for systems of the future. What does it mean to verify these massively integrated systems, with new features, new models of computation, non-Traditional architectures and new applications? How do we characterize, define, execute and sign off on the correctness of the most complex systems known to humans? This paper touches upon these questions and presents challenges in these systems of the future.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781538615539
DOIs
StatePublished - Nov 28 2017
Event2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Washington, United States
Duration: Nov 8 2017Nov 9 2017

Publication series

Name2017 IEEE International Conference on Rebooting Computing, ICRC 2017 - Proceedings
Volume2017-January

Other

Other2017 IEEE International Conference on Rebooting Computing, ICRC 2017
CountryUnited States
CityWashington
Period11/8/1711/9/17

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Statistical and Nonlinear Physics
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Hardware and Architecture
  • Software

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