Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …

Research in photonic computing has flourished due to the proliferation of optoelectronic
components on photonic integration platforms. Photonic integrated circuits have enabled …

Artificial intelligence tasks across numerous applications require accelerators for fast and
low-power execution. Optical computing systems may be able to meet these domain-specific …

Neural networks have enabled applications in artificial intelligence through machine
learning, and neuromorphic computing. Software implementations of neural networks on …

The explosive growth of deep learning applications has triggered a new era in computing
hardware, targeting the efficient deployment of multiply-and-accumulate operations. In this …

With an ongoing trend in computing hardware toward increased heterogeneity, domain-
specific coprocessors are emerging as alternatives to centralized paradigms. The tensor …

In recent years, the computational demands of deep learning applications have necessitated
the introduction of energy-efficient hardware accelerators. Optical neural networks are a …

We demonstrate a passive all-chalcogenide all-optical perceptron scheme. The network's
nonlinear activation function (NLAF) relies on the nonlinear response of Ge2Sb2Te5 to …

In this study, indium tin oxide (ITO) films (~ 350 nm) were prepared using the electron beam
gun technology. Influence of thermal treatment of the films at a variety of temperatures on the …

The high demand for machine intelligence of doubling every three months is driving novel
hardware solutions beyond charging of electrical wires, given a resurrection to application …