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 ...
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 ...
“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-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 ...
A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a ...
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