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 …

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 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 …

In this paper we report the design of a device allowing on-chip optical wireless
interconnections, based on transmitting and receiving Optical Phased Arrays (OPA). The …

Enhancing performance while reducing costs is the fundamental design philosophy of
integrated circuits (ICs). With advancements in packaging technology, interposer-based …

Phase Change Memory (PCM) is an attractive candidate for main memory, as it offers non-
volatility and zero leakage power while providing higher cell densities, longer data retention …

Optical on-chip wireless interconnection is an emerging technology that aims to overcome
the communication bottleneck in computing architectures and in which multiple processing …