In this video from PASC17, Alfio Lazzaro (University of Zurich, Switzerland) presents: Increasing Efficiency of Sparse Matrix-Matrix Multiplication. “Matrix-matrix multiplication is a basic operation ...
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 ...
A custom matrix multiplication implementation using De Bruijn graphs and optimized vector operations. This crate provides an alternative to OpenBLAS for matrix operations, with a focus on sparse ...
Abstract: We demonstrate a space-wavelength-time multiplexed optical tensor processor based on the chromatic dispersion of free-space diffraction grating. Parallel matrix-matrix multiplication with 64 ...
Abstract: Matrix multiplication is an essential operation in the field of mathematics and computer science. Many critical computations, such as matrix factorization and graph computations, cast the ...
The most widely used matrix-matrix multiplication routine is GEMM (GEneral Matrix Multiplication) from the BLAS (Basic Linear Algebra Subroutines) library. And these days it can be found being used in ...
Hefei National Laboratory for Physical Sciences at the Microscale, Department of Chemical Physics, and Synergetic Innovation Center of Quantum Information and Quantum Physics, University of Science ...
The matrix multiplication infix operator (*) produces a new matrix by performing matrix multiplication. The first matrix must have the same number of columns as the second matrix has rows. The new ...
Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...
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