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AI Chips Built by AI - Promise or Reality?: An Industry Perspective

Published: 12 September 2022 Publication History

Abstract

Artificial Intelligence is an avenue to innovation that is touching every industry worldwide. AI has made rapid advances in areas like speech and image recognition, gaming, and even self-driving cars, essentially automating less complex human tasks. In turn, this demand drives rapid growth across the semiconductor industry with new chip architectures emerging to deliver the specialized processing needed for the huge breadth of AI applications. Given the advances made to automate simple human tasks, can AI solve more complex tasks such as designing a computer chip? In this talk, we will discuss the challenges and opportunities of building advanced chip designs with the help of artificial intelligence, enabling higher performance, faster time to market, and utilizing reuse of machine-generated learning for successive products.

References

[1]
https://www.synopsys.com/implementation-and-signoff/ml-ai-design.html
[2]
https://www.synopsys.com/ai.html

Cited By

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  • (2024) AI Chain 2024 6th International Conference on Blockchain Computing and Applications (BCCA)10.1109/BCCA62388.2024.10844498(497-504)Online publication date: 26-Nov-2024

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  1. AI Chips Built by AI - Promise or Reality?: An Industry Perspective

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    cover image ACM Conferences
    MLCAD '22: Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD
    September 2022
    181 pages
    ISBN:9781450394864
    DOI:10.1145/3551901
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 12 September 2022

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    Author Tags

    1. artificial intelligence
    2. deep learning
    3. floorplanning
    4. logic design
    5. machine learning
    6. physical design
    7. physical verification
    8. reinforcement learning

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    • Invited-talk

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    MLCAD '22
    Sponsor:
    MLCAD '22: 2022 ACM/IEEE Workshop on Machine Learning for CAD
    September 12 - 13, 2022
    Virtual Event, China

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    Overall Acceptance Rate 35 of 83 submissions, 42%

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    Cited By

    View all
    • (2024) AI Chain 2024 6th International Conference on Blockchain Computing and Applications (BCCA)10.1109/BCCA62388.2024.10844498(497-504)Online publication date: 26-Nov-2024

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