With the down-scaling of CMOS technology, the design complexity of very large-scale
integrated is increasing. Although the application of machine learning (ML) techniques in …

The technology of big data analysis and artificial intelligence deep learning has been
actively cross-combined with various fields to increase the effect of its original low single …

As the circuit feature size continuously shrinks down, hotspot detection has become a more
challenging problem in modern DFM flows. Developed deep learning techniques have …

With continued scaling, the transistor aging induced by hot carrier injection (HCI) and bias
temperature instability (BTI) causes an increasing failure of nanometer-scale integrated …

Due to advances in semiconductor processing technologies, wafer failure pattern detection
plays a key role in preventing yield loss excursion events for semiconductor manufacturing …

Adders are the primary components in the data-path logic of a microprocessor, and thus,
adder design has been always a critical issue in the very large-scale integration (VLSI) …

The increasing complexity and size of design space poses significant challenges for
integrated circuit (IC) design. This article discusses the potential of machine learning (ML) …

Inverse Lithography Technology (ILT) is a widely investigated method to improve the yield of
chip manufacturing. However, high computational complexity and difficulty in fabricating …

Compared with traditional convolutions, grouped convolutional neural networks are
promising for both model performance and network parameters. However, existing models …

Modern designs are increasingly reliant on physical design (PD) tools to derive full
technology scaling benefits of Moore's Law. Designers often perform power, performance …