Tech Xplore

Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...
The Malaysian Reserve

MicroCloud Hologram Inc. Utilizes FPGA to Accelerate Tensor Network Computing to Achieve Quantum Spin Models

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, proposed an innovative hardware acceleration technology that converts the quantum tensor network ...
IEEE

Performance and Power Characteristics of Matrix Multiplication Algorithms on Multicore and Shared Memory Machines

Abstract: For many scientific applications, dense matrix multiplication is one of the most important and computation intensive linear algebra operations. An efficient matrix multiplication on high ...
IEEE

ScanNow: A Scan Window-Based Sparse Matrix Multiplication Accelerator Design

Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...
GitHub

Feroz455/Fundamentals-of-Computer-Algorithms-2nd-Edition-by-Ellis-Horowitz-Sartaj-Sahni-and-Sanguthevar

This repository contains comprehensive implementations of algorithms from the classic textbook "Fundamentals of Computer Algorithms" (Second Edition) by Ellis Horowitz, Sartaj Sahni, and Sanguthevar ...