Computing is a critical driving force in the development of human civilization. In recent years,
we have witnessed the emergence of intelligent computing, a new computing paradigm that …

In the modern-day era of technology, a paradigm shift has been witnessed in the areas
involving applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep …

Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …

Photonic computing enables faster and more energy-efficient processing of vision data,,,–.
However, experimental superiority of deployable systems remains a challenge because of …

New developments in hardware-based 'accelerators' range from electronic tensor cores and
memristor-based arrays to photonic implementations. The goal of these approaches is to …

Analog in-memory computing—a promising approach for energy-efficient acceleration of
deep learning workloads—computes matrix-vector multiplications but only approximately …

This paper updates the survey of AI accelerators and processors from past three years. This
paper collects and summarizes the current commercial accelerators that have been publicly …

Technology solutions must effectively balance economic growth, social equity, and
environmental integrity to achieve a sustainable society. Notably, although the Internet of …

Deep neural network (DNN) training workloads are increasingly susceptible to hardware
failures in datacenters. For example, Google experienced" mysterious, difficult to identify …

We examine the computational energy requirements of different systems driven by the
geometrical scaling law (known as Moore's law or Dennard Scaling for geometry) and …