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 ...

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 ...

“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 ...

Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...

Abstract: Mixed-precision computation, which uses multiple different precision in a single code, is being studied to increase computational speed and energy efficiency. It typically uses the IEEE ...

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 ...

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 ...