One of the biggest stakes in nanoelectronics today is to meet the needs of Artificial
Intelligence by designing hardware neural networks which, by fusing computation and …

Abstract Deep Neural Networks (DNN) have proven to be highly effective in extracting high
level abstractions of input data using multiple neural network layers. However, the huge …

One popular approach under approximate computing is stochastic computing, wherein
values are encoded in bitstreams to perform arithmetic operations in a low-power and …

We discuss a convolutional neural network for handwritten digit classification and its
hardware acceleration as an inference engine using nanoscale memristive devices in the …

The human brain, with its massive computational capability and power efficiency in small
form factor, continues to inspire the ultimate goal of building machines that can perform tasks …

The deep learning approach to AI has taken upon the whole society thanks to the use of
Graphical Computing Units (GPUs). Going beyond the capability of the GPUs for deep …

(57) ABSTRACT A computer-implemented method is presented for perform ing matrix
sketching by employing an analog crossbar architecture. The method includes low rank …

Abstract Machine Learning has permeated many aspects of engineering, ranging from the
Internet of Things (IoT) applications to big data analytics. While computing resources …