David Pan

Artificial intelligence (AI) studies the theory and development of computing systems able to learn, reason, act and adapt. Integrated circuit (ICs), powered by the semiconductor technology, enable all modern computing systems with an amazing level of integration, e.g., a small chip (<1cm²) nowadays can integrate billions of transistors. As the semiconductor technology enters the era of extreme scaling (1x nm), IC design and manufacturing complexities are extremely high. Intelligent cross-layer design and manufacturing co-optimizations are in critical demand for better performance, power, yield, reliability, security, time-to-market, and so on. This talk will discuss the synergy between modern AI technologies (e.g., deep learning) with intelligent deep-nanoscale IC design and manufacturing. Several case studies will be presented in terms of AI for IC, including advanced lithography modeling, mask synthesis, physical design, and security. Meanwhile, customized ICs for AI can further improve the training and inference performance-energy efficiency by orders of magnitude. Thus, the co-evolution of AI algorithms and IC technologies shall be investigated jointly to enhance the research and development of each other.

Despite tremendous advancement of digital IC CAD tools over the last few decades, analog IC layout is still heavily manual which is very tedious and error-prone. This talk will discuss the overall objective and preliminary results of MAGICAL, a human-intelligence inspired, fully-automated analog IC layout tool sponsored by the DARPA IDEA program. MAGICAL starts from an unannotated netlist, perform automatic layout constraint generation and device generation, then perform automatic placement, legalization, well generation, followed by automatic routing (including signal and power/clock routing) to obtain GDSII, guided by various analytical, heuristic, and machine learning algorithms. MAGICAL has obtained promising initial results. It will be made open source to the public later in 2019. I will also discuss challenges and future directions.

The advancement of photonic integrated circuits (PICs) brings new opportunities for optical computing. Optical computing, as a promising alternative to traditional CMOS computing, has great potentials to offer ultra-high speed and low-power in information processing and communications. This seminar will discuss some recent efforts and results on optical computing on PICs, including optical adder/multiplier designs, optical logic synthesis, and optical neural network. The advantages, limitations, and possible research directions will be discussed.