In pursuit of higher inference accuracy, deep neural network (DNN) models have
significantly increased in complexity and size. To overcome the consequent computational …

Chiplet-based convolution neural network (CNN) accelerators have emerged as a promising
solution to provide substantial processing power and on-chip memory capacity for CNN …

The complexity and size of recent deep neural network (DNN) models have increased
significantly in pursuit of high inference accuracy. Chiplet-based accelerator is considered a …

Silicon photonics technology is now gaining maturity with increasing levels of design
complexity from devices to large photonic integrated circuits. Close integration of control …

Chiplet-based architectures have been proposed to scale computing systems for deep
neural networks (DNNs). Prior work has shown that for the chiplet-based DNN accelerators …

2.5-D integration technology is gaining attention and popularity in manycore computing
system design. 2.5-D systems integrate homogeneous or heterogeneous chiplets in a …

Thermal analysis is an essential step that enables co-design of the computing system (ie,
integrated circuits and computer architectures) with the cooling system (eg, heat sink) …

2.5-D manycore systems running parallel applications are severely bottlenecked by network-
on-chip (NoC) latencies and bandwidth. Traditionally, NoCs are composed of electrical links …

2.5 D chiplet systems have been proposed to improve the low manufacturing yield of large-
scale chips. However, connecting the chiplets through an electronic interposer imposes a …

Knowledge graphs (KGs) have achieved significant attention in recent years, particularly in
the area of the Semantic Web as well as gaining popularity in other application domains …