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 ...

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 ...

This repository contains the SystemVerilog code and simulation results for a systolic array-based matrix-vector multiplication for signed 8 bit integers. The architecture is designed to perform the ...

Abstract: We consider the distributed memory parallel multiplication of a sparse matrix by a dense matrix (SpMM). The dense matrix is often a collection of dense vectors. Standard implementations will ...

-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 ...

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 ...