Photonic innovation: researchers in the US have created an optical metamaterial that can perform vector–matrix multiplication. (Courtesy: iStock/Henrik5000) A new silicon photonics platform that can ...

-Sparse matrix-vector multiplication is a crucial operation in scientific computing, machine learning and deep learning. Data that is used in computation & simulation are most in the form of sparse ...

Abstract: On-chip optical neural networks (ONNs) have recently emerged as an attractive hardware accelerator for deep learning applications, characterized by high computing density, low latency, and ...

This project demonstrates how a resistive crossbar can be used to perform matrix-vector multiplication. The goal is to simulate a 4x4 resistive crossbar in SPICE, where the resistances at each ...

Abstract: Structured sparsity has been proposed as an efficient way to prune the complexity of Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. Accelerating ...

Optical computing uses photons instead of electrons to perform computations, which can significantly increase the speed and energy efficiency of computations by overcoming the inherent limitations of ...

“Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks and can yield ...