GitHub

A Python demonstration of speeding up matrix multiplication and reducing memory using a quantum-inspired low-rank SVD trick, with examples in AI.

This repository demonstrates a powerful, classical linear algebra technique—low-rank approximation via Singular Value Decomposition (SVD)—to dramatically accelerate common matrix operations like GEMM ...
GitHub

Matrix multiplication in CVXPY 1.1

in the Jupyter-Notebook "DMC_Capacity.ipynb" from the lecture CC_GBC, i get the folowing hint: This use of ``*`` has resulted in matrix multiplication. Using ``*`` for matrix multiplication has been ...
IEEE

Inverse-Designed Photonic Computing Core for Parallel Matrix-Vector Multiplication

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 ...
IEEE

GAS: General-Purpose In-Memory-Computing Accelerator for Sparse Matrix Multiplication

Abstract: Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV), sparse ...