an Artificial Intelligence Approach to Vlsi Design

In 1984, while I was following his postgraduate course on VLSI design, my supervisor Dr. David Skellern, asked me if I was interested in investigating intelligent approaches to automatic Ie floorplanning. He told me then: "a circuit that works always looks nice, has a clever data and control flow.

This book, and the research it describes, resulted from a simple observation we made sometime in 1986. Put simply, we noticed that many VLSI design tools looked "alike". That is, at least at the overall software architecture level, the algorithms and data structures required to solve problem X looked much like those required to solve problem X'. Unfortunately, this resemblance is often of little help in actually writing the software for problem X' given the software for problem X. In the VLSI CAD world, technology changes rapidly enough that design software must continually strive to keep up. And of course, VLSI design software, and engineering design software in general, is often exquisitely sensitive to some aspects of the domain (technology) in which it operates. Modest changes in functionality have an unfortunate tendency to require substantial (and time-consuming) internal software modifications. Now, observing that large engineering software systems are technology­ dependent is not particularly clever. However, we believe that our approach to xiv Preface dealing with this problem took an interesting new direction. We chose to investigate the extent to which automatic programming ideas cold be used to synthesize such software systems from high-level specifications. This book is one of the results of that effort.

This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, the efficient hardware of machine learning applications with FPGA or CMOS circuits, and many other aspects and applications of machine learning techniques for VLSI chip design.

This book describes cutting-edge developments and advances in theory, methodology and applications of computer science and engineering. Written by leading experts in the field

by Wujie Zhang (Author)
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs).