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 ...

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 ...

There has been an ever-growing demand for artificial intelligence and fifth-generation communications globally, resulting in very large computing power and memory requirements. The slowing down or ...

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 ...

Israeli start-up 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 ...

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 ...