The rapid development of artificial intelligence (AI) demands the rapid development of
domain-specific hardware specifically designed for AI applications. Neuro-inspired …

Traditional von Neumann computing systems involve separate processing and memory
units. However, data movement is costly in terms of time and energy and this problem is …

The rapid increase in information in the big-data era calls for changes to information-
processing paradigms, which, in turn, demand new circuit-building blocks to overcome the …

Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

Software implementations of brain-inspired computing underlie many important
computational tasks, from image processing to speech recognition, artificial intelligence and …

Neuromorphic computing has emerged as a promising avenue towards building the next
generation of intelligent computing systems. It has been proposed that memristive devices …

This comprehensive review summarizes state of the art, challenges, and prospects of the
neuro-inspired computing with emerging nonvolatile memory devices. First, we discuss the …

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …

This article presents C3SRAM, an in-memory-computing SRAM macro. The macro is an
SRAM module with the circuits embedded in bitcells and peripherals to perform hardware …

Neuromorphic computing is henceforth a major research field for both academic and
industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at …