AI/ML Algorithms and Applications in VLSI Design and Technology
AI/ML Algorithms and Applications in VLSI Design and Technology
微电子学、集成电路
Zia Abbas,Sushanth R. Gurram,Andleeb Zahra,Harsha V. Vudumula,Pavan K. Cherupally,Deepthi Amuru,Amir Ahmad.AI/ML Algorithms and Applications in VLSI Design and Technology[EB/OL].(2022-02-21)[2025-09-24].https://arxiv.org/abs/2202.10015.点此复制
An evident challenge ahead for the integrated circuit (IC) industry in the
nanometer regime is the investigation and development of methods that can
reduce the design complexity ensuing from growing process variations and
curtail the turnaround time of chip manufacturing. Conventional methodologies
employed for such tasks are largely manual; thus, time-consuming and
resource-intensive. In contrast, the unique learning strategies of artificial
intelligence (AI) provide numerous exciting automated approaches for handling
complex and data-intensive tasks in very-large-scale integration (VLSI) design
and testing. Employing AI and machine learning (ML) algorithms in VLSI design
and manufacturing reduces the time and effort for understanding and processing
the data within and across different abstraction levels via automated learning
algorithms. It, in turn, improves the IC yield and reduces the manufacturing
turnaround time. This paper thoroughly reviews the AI/ML automated approaches
introduced in the past towards VLSI design and manufacturing. Moreover, we
discuss the scope of AI/ML applications in the future at various abstraction
levels to revolutionize the field of VLSI design, aiming for high-speed, highly
intelligent, and efficient implementations.
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