For many decades, progress in computing hardware has been closely associated with
CMOS logic density, performance, and cost. As such, slowdown in 2-D scaling, frequency …

The remarkable breakthroughs in deep learning have led to a dramatic thirst for
computational resources to tackle interesting real-world problems. Various neural network …

Convolutional neural networks (CNNs) have gained a massive impression in the fields of
computer vision and especially in the embedded applications because of their high …

This book describes the first comprehensive approach to the optimization of interconnect
architectures in 3D systems on chips (SoCs), specially addressing the challenges and …

Convolutional neural networks (CNNs) have gained a massive appreciation recently, due to
their high efficiency in applications ranging from classification and segmentation of images …

Before discussing the modeling and optimization of 3D interconnect architectures for
heterogeneous technologies in detail, it is advisable to overview the key ideas of 3D …

The global interconnects are one of the most fundamental bottlenecks in modern systems on
chips (SoCs). They determine to a large degree the performance and energy consumption of …

The past decade has seen a tremendous surge in running machine learning (ML) functions
on mobile devices, from mere novelty applications to now indispensable features for the next …