They break large matrix problems into smaller segments and solve them simultaneously using an algorithm. Improvements to this algorithm have been key to breakthroughs in matrix multiplication ...

In particular, we extend the DBCSR sparse matrix library, which is the basic building block for linear scaling electronic structure theory and low scaling correlated methods in CP2K. The library is ...

Nearly all big science, machine learning, neural network, and machine vision applications employ algorithms that involve large matrix-matrix multiplication. But multiplying large matrices pushes the ...

Photonic accelerators have been widely designed to accelerate some specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for ...

An adapted alternating treatments design was used to compare the effectiveness of a taped-problems (TP) intervention with TP and an additional immediate assessment (TP + AIA) on the multiplication ...