Trends in Semiconductor Design Verification for AI and Machine Learning Applications

Author(s)	Niranjana Gurushankar
Country	United States
Abstract	The rapid evolution of Artificial Intelligence (AI) and Machine Learning (ML) is driving a surge in complex semiconductor designs. These designs, crucial for applications ranging from autonomous vehicles to personalized medicine, demand rigorous verification to ensure functionality and reliability. This paper explores the latest trends in semiconductor design verification for AI/ML applications, addressing the unique challenges posed by these computationally intensive and data-driven systems. We examine the shift towards formal verification techniques, the increasing use of hardware acceleration for simulation, and the growing importance of security verification in AI/ML chips. Further, we analyze the role of emerging methodologies like emulation and prototyping in validating AI/ML hardware. By delving into these trends, we aim to provide insights into the evolving landscape of semiconductor design verification and its crucial role in enabling the next generation of AI/ML innovations.
Keywords	AI, Machine Learning, Semiconductor, Design Verification, Formal Verification, Hardware Acceleration, Emulation, Prototyping, Security Verification
Field	Lainnya
Published In	Volume 4, Issue 6, November-December 2022
Published On	2022-11-15
DOI	https://doi.org/10.36948/ijfmr.2022.v04i06.23501
Short DOI	https://doi.org/g82h5f

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