Nanowerk

Stacked memristor arrays compute Euclidean distance in memory to accelerate self-organizing maps

A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
Semiconductor Engineering

In-Memory Computing: Assessing Multilevel RRAM-Based VMM Operations

A new technical paper titled “Experimental Assessment of Multilevel RRAM-Based Vector-Matrix Multiplication Operations for In-Memory Computing” was published by researchers at IHP (the Leibniz ...
Semiconductor Engineering

Large-Scale Integration Of 2D Materials As The Semiconducting Channel In An In-Memory Processor (EPFL)

A technical paper titled “A large-scale integrated vector-matrix multiplication processor based on monolayer molybdenum disulfide memories” was published by researchers at École Polytechnique Fédérale ...
insideHPC

Sparse Matrix Multiplication

Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...
EDN

Engine solves matrix calculation in single cycle

Israeli startup Lenslet Labs has gone back to the fundamentals of mathematics to develop a processing engine that can handle matrix calculations natively without having to break them down into many ...
Simon Fraser University

Image Matrix Transformations

If \(A\) is a \(3\times 3\) matrix then we can apply a linear transformation to each rgb vector via matrix multiplication, where \([r,g,b]\) are the original values ...