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 …

In this review the different concepts of nanoscale resistive switching memory devices are
described and classified according to their I–V behaviour and the underlying physical …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

The availability of unprecedented unsupervised training data, along with neural scaling
laws, has resulted in an unprecedented surge in model size and compute requirements for …

The growing importance of applications based on machine learning is driving the need to
develop dedicated, energy-efficient electronic hardware. Compared with von Neumann …

Data-driven algorithms—such as signal processing and artificial neural networks—are
required to process and extract meaningful information from the massive amounts of data …

Modern computing systems are overwhelmingly designed to move data to computation. This
design choice goes directly against at least three key trends in computing that cause …

Today's systems are overwhelmingly designed to move data to computation. This design
choice goes directly against at least three key trends in systems that cause performance …

In-memory computing has long been promised as a solution to the" Memory Wall" problem.
Recent work has proposed using chargesharing on the bit-lines of a memory in order to …

Data movement between the CPU and main memory is a first-order obstacle against improv
ing performance, scalability, and energy efficiency in modern systems. Computer systems …