Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …

A memristor is a resistive device with an inherent memory. The theoretical concept of a
memristor was connected to physically measured devices in 2008 and since then there has …

Recent progress in artificial intelligence is largely attributed to the rapid development of
machine learning, especially in the algorithm and neural network models. However, it is the …

The semiconductor industry continues to produce ever smaller devices that are ever more
complex in shape and contain ever more types of materials. The ultimate sizes and …

As the limits of transistor technology are approached, feature size in integrated circuit
transistors has been reduced very near to the minimum physically-realizable channel length …

Computers have undergone tremendous improvements in performance over the last 60
years, but those improvements have significantly slowed down over the last decade, owing …

Historically, memory technologies have been evaluated based on their storage density, cost,
and latencies. Beyond these metrics, the need to enable smarter and intelligent computing …

As data movement operations and power-budget become key bottlenecks in the design of
computing systems, the interest in unconventional approaches such as processing-in …

Large-scale digital computing almost exclusively relies on the von Neumann architecture,
which comprises separate units for storage and computations. The energy-expensive …